# XII. EVIDENCE

This page defines Nexus Foundry evidence architecture for governed review, testing, simulation-first production, evidence products, and proof, provenance, and verifiable compute. It explains the review matrix, testing architecture, simulation-first production model, evidence products, and proof and provenance controls used to keep governed public-good software, public-safe outputs, and provider-neutral systems traceable, reviewable, correctionable, and supportable.

### Summary

* Nexus Foundry evidence architecture governs the review matrix, testing architecture, simulation-first production, and proof by record.
* The model keeps evidence products, public-safe communication, proof and provenance, and verifiable compute traceable across the lifecycle.
* Evidence status does not create certification, procurement, financeability, deployment approval, or execution authority.

### Read this with

* [NEXUS FOUNDRY](/organization/acceleration/nexus-foundry.md)
* [IX. PRODUCTION](/organization/acceleration/nexus-foundry/ix.-production.md)
* [X. OPERATIONS](/organization/acceleration/nexus-foundry/x.-operations.md)
* [XI. PORTFOLIO](/organization/acceleration/nexus-foundry/xi.-portfolio.md)
* [XIII. READINESS](/organization/acceleration/nexus-foundry/xiii.-readiness.md)
* [XIV. RELEASE](/organization/acceleration/nexus-foundry/xiv.-release.md)

### In this evidence model

* [Foundry Review Architecture](#65-foundry-review-architecture)
* [Testing Architecture](#66-testing-architecture)
* [Simulation-First Production](#67-simulation-first-production)
* [Evidence Products](#68-evidence-products)
* [Proof, Provenance, and Verifiable Compute](#69-proof-provenance-and-verifiable-compute)

## 65. Foundry Review Architecture

### 65.1 Review Matrix

**65.1.1 Review Matrix Identity.** The **Foundry Review Matrix** shall be the governed, record-bearing architecture that determines which reviews are required, optional, conditional, escalated, repeated, waived, restricted, or archived for each Foundry Object, Product Line, Rail, Pack, Profile, Schema, Connector, Agent, Dashboard, Evidence Product, Readiness Product, Safeguard Product, Deployment Unit, Marketplace Object, Registry Object, Studio Runtime Package, National Portfolio object, Core Build output, Nexus Universe output, public-safe material, support record, correction record, and lawful handoff dependency package.

**65.1.2 Review Matrix Purpose.** The Review Matrix shall prevent Foundry work from moving by informal judgment, contributor enthusiasm, event urgency, sponsor pressure, provider readiness, public authority ambiguity, capital-reader interest, internal prestige, or technical convenience. It shall make review obligations visible before work enters production, release, public-safe publication, Marketplace listing, Registry recording, Studio runtime, National Portfolio use, Core Build use, Nexus Universe presentation, readiness mapping, support, correction, handoff preparation, or archive.

**65.1.3 Review Matrix Record.** Each material object shall have a **Review Matrix Record** identifying object class, risk class, required reviews, conditional reviews, review sequence, review dependencies, reviewer roles, independence requirements, conflict requirements, escalation triggers, public-safe triggers, national routing triggers, safeguard triggers, data triggers, AI triggers, cyber triggers, public authority triggers, finance triggers, procurement triggers, community triggers, Indigenous protocol triggers where applicable, legal or jurisdictional triggers, release triggers, support triggers, archive triggers, correction pathway, and prohibited interpretations.

**65.1.4 Review Types.** The Review Matrix may include Evidence Review, Technical Review, Architecture Review, Ontology and Schema Review, Data Review, Cyber Review, AI Review, Dual-Use Review, Public-Safe Review, Public Authority Boundary Review, Finance Boundary Review, Procurement Neutrality Review, Community Safeguard Review, Indigenous Protocol Review where applicable, Legal and Jurisdictional Review, Release Review, Support Review, Archive Review, Correction Review, Provider-Neutrality Review, Accessibility Review, Translation Review, Reliability Review, Reproducibility Review, and Teardown Review.

**65.1.5 Risk-Based Review.** Reviews shall be proportionate to object class, data sensitivity, public-safe sensitivity, AI autonomy, cyber exposure, public authority relevance, finance or procurement relevance, community impact, Indigenous protocol relevance where applicable, national routing relevance, provider dependency, support burden, release class, Marketplace visibility, Registry status, Studio runtime, Core Build exposure, Nexus Universe visibility, and handoff proximity. Low-risk work may receive light review; high-risk work shall receive layered review.

**65.1.6 Review Sequence.** Review sequence shall be recorded where order matters. Data Review may precede AI Review. Safeguard Review may precede Public-Safe Review. Evidence Review may precede Readiness Review. Public Authority Boundary Review may precede public authority learning use. Finance Boundary Review may precede capital-reader-facing materials. Release Review may not override unresolved blocking reviews.

**65.1.7 Most-Restrictive Review Rule.** Where review requirements are ambiguous, the most restrictive reasonable review pathway shall apply until corrected by competent record. Ambiguity shall not be used to accelerate release, publication, Marketplace listing, Registry status, Studio runtime, public authority learning, finance-readable communication, National Portfolio display, handoff preparation, deployment implication, or execution implication.

**65.1.8 Review Matrix Boundary.** Review Matrix assignment, review completion, positive review note, review clearance, non-blocking finding, conditional finding, or review status shall not create certification, accreditation, public authority approval, procurement status, financeability, insurability, maturity certification, consent, deployment authorization, operational command, or execution authority unless a separate competent process expressly creates that status outside default Foundry.

**65.1.9 Review Matrix Correction.** Review Matrix Records shall be corrected where reviews are omitted, wrong review sequence is applied, conflicts are undisclosed, review scope is overstated, public-safe triggers are missed, safeguard triggers are missed, national routing is bypassed, provider influence affects review, or review completion is represented as approval, certification, maturity, finance, procurement, consent, deployment, or execution.

**65.1.10 Review Matrix Formula.** The Review Matrix shall follow the formula: **classify the object; identify required reviews by risk and pathway; sequence reviews by dependency; disclose conflicts; apply the most restrictive rule under uncertainty; correct review drift; never let review architecture become certification, approval, consent, deployment, or execution authority.**

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### 65.2 Evidence Review

**65.2.1 Evidence Review Identity.** **Evidence Review** shall be the governed review of source records, evidence quality, methods, assumptions, uncertainty, limitations, reproducibility, traceability, data provenance, model provenance, benchmark scope, simulation scope, public-safe evidence summaries, Evidence Products, Readiness Products, Observatory outputs, DRI outputs, GRIx context, dashboards, Studio materials, Marketplace descriptions, Registry references, National Portfolio materials, and handoff dependency packages.

**65.2.2 Evidence Review Purpose.** Evidence Review shall ensure that Foundry claims are supported by records and that unsupported claims are blocked, revised, limited, restricted, withdrawn, or archived. Evidence Review shall protect Foundry from treating incomplete research, provider materials, sponsor narratives, AI summaries, demonstration results, benchmark fragments, anecdotal inputs, or event outputs as institutional truth.

**65.2.3 Evidence Review Record.** Each Evidence Review shall have an Evidence Review Record identifying evidence question, object reviewed, sources reviewed, source quality, method used, data provenance, AI involvement where applicable, benchmark or simulation scope where applicable, uncertainty, limitations, assumptions, reviewer, conflicts, accepted evidence, rejected evidence, required corrections, downstream limits, archive rule, and prohibited interpretations.

**65.2.4 Evidence Review Criteria.** Evidence Review shall assess whether sources are traceable, current enough for purpose, relevant, methodologically appropriate, non-duplicative, not selectively interpreted, not provider-captured, not sponsor-captured, not generalized beyond scope, and not presented without uncertainty or limitation. Evidence Review shall distinguish fact, inference, assumption, judgment, scenario, hypothesis, model output, and recommendation.

**65.2.5 Evidence Review for AI Outputs.** AI-generated or AI-assisted evidence summaries shall be reviewed against source records. AI output shall not be treated as evidence source by itself. Where AI assisted the review, the record shall identify the role of AI, human review, source-checking, limitations, and correction path.

**65.2.6 Evidence Review for Public Materials.** Evidence underlying public-safe materials shall be reviewed for source sufficiency, public-safe meaning, confidence, uncertainty, drift, limitation language, and no-conversion language. Public-facing evidence claims shall not exceed the record.

**65.2.7 Evidence Review Boundary.** Evidence Review completion, evidence sufficiency note, benchmark review, method review, or evidence product acceptance shall not create scientific consensus, certification, validation for all contexts, public authority approval, procurement status, financeability, insurability, maturity status, consent, deployment authorization, or execution authority.

**65.2.8 Evidence Review Correction.** Evidence Review Records shall be corrected where sources change, methods are found flawed, uncertainty is understated, limitations are omitted, evidence is generalized beyond scope, provider or sponsor materials are over-weighted, AI output is uncritically accepted, or Evidence Review is used as approval.

**65.2.9 Evidence Review Formula.** Evidence Review shall follow the formula: **trace every claim to records; separate evidence from inference; state uncertainty and limits; block unsupported claims; correct evidence drift; never let evidence review become certification, public authority approval, financeability, procurement status, consent, deployment, or execution.**

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### 65.3 Technical Review

**65.3.1 Technical Review Identity.** **Technical Review** shall be the governed review of technical correctness, maintainability, interoperability, dependency structure, performance within scope, test adequacy, integration behavior, version control, documentation alignment, supportability, portability, provider neutrality, and lifecycle readiness for Foundry technical objects, including code, scripts, connectors, APIs, schemas, agents, dashboards, infrastructure templates, Golden Images, data-room tools, secure-room tools, Observatory modules, Studio runtime packages, Marketplace objects, Registry integrations, and Deployment Units.

**65.3.2 Technical Review Purpose.** Technical Review shall determine whether a technical object is built according to its recorded specification and whether it can proceed to the next Foundry stage within its recorded limits. It shall not determine that the object is safe, compliant, deployable, procurement-ready, financeable, or operationally authorized in all contexts.

**65.3.3 Technical Review Record.** Each Technical Review shall have a Technical Review Record identifying object, version, specification, source records, code or configuration reviewed, dependency inventory, test status, interoperability status, portability status, documentation status, support implications, reviewer, conflicts, findings, accepted elements, rejected elements, required corrections, release limits, archive rule, and prohibited interpretations.

**65.3.4 Technical Review Criteria.** Technical Review shall assess correctness, modularity, code quality, configuration quality, dependency risk, interoperability, portability, test coverage, reproducibility, logging where appropriate, error handling, documentation alignment, maintainability, support burden, provider-neutrality, license compatibility, and teardown feasibility.

**65.3.5 Integration Review.** Technical Review shall examine not only individual components but also the integrated behavior of Builds, Packs, Deployment Units, Studio Runtime Packages, dashboards, connectors, agents, and Observatory pipelines. A technically acceptable component shall not automatically make the assembled object acceptable.

**65.3.6 Technical Review and Provider Dependencies.** Technical Review shall identify provider-specific assumptions, proprietary components, managed service dependencies, cloud dependencies, model dependencies, hardware dependencies, and substitution limits. Technical convenience shall not hide provider lock-in.

**65.3.7 Technical Review Boundary.** Technical Review completion, code acceptance, test pass, benchmark pass, architecture fit, repository merge, or technical release-candidate status shall not create certification, procurement status, financeability, public authority approval, maturity status, consent, deployment authorization, operational readiness, or execution authority.

**65.3.8 Technical Review Correction.** Technical Review Records shall be corrected where dependencies become unsafe, code introduces vulnerabilities, integration behavior changes, documentation becomes stale, tests are insufficient, provider lock-in is hidden, support burden is understated, or Technical Review is treated as deployment approval.

**65.3.9 Technical Review Formula.** Technical Review shall follow the formula: **review against specification; test within scope; examine dependencies and integration; state support limits; correct technical drift; never let technical acceptance become certification, procurement, finance, consent, deployment, or execution.**

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### 65.4 Architecture Review

**65.4.1 Architecture Review Identity.** **Architecture Review** shall be the governed review of Foundry system architecture, reference architecture, control plane, data plane, compute plane, network plane, security plane, AI / agentic systems plane, observability plane, repository plane, release plane, publication plane, Marketplace plane, Registry plane, Studio runtime plane, support plane, correction plane, archive plane, teardown plane, and lawful handoff pathway architecture.

**65.4.2 Architecture Review Purpose.** Architecture Review shall ensure that Foundry objects and Product Lines fit the Nexus architecture without creating role collapse, provider capture, hidden execution, uncontrolled data movement, unsupported runtime, public authority substitution, finance execution, procurement implication, consent overclaim, or deployment authority by design.

**65.4.3 Architecture Review Record.** Each Architecture Review shall have an Architecture Review Record identifying object or Product Line, architectural scope, planes affected, reference architecture pattern, dependencies, integration points, control boundaries, data boundaries, compute boundaries, network boundaries, security boundaries, AI boundaries, observability boundaries, Marketplace / Registry / Studio boundaries, national routing, support implications, handoff implications, reviewer, conflicts, findings, required corrections, archive rule, and prohibited interpretations.

**65.4.4 Architecture Review Criteria.** Architecture Review shall assess modularity, separation of concerns, control-plane integrity, data-plane controls, compute placement, network segmentation, security architecture, AI tool boundaries, Observatory visibility boundaries, Marketplace / Registry / Studio separation, provider-neutrality, open baseline alignment, national localization, supportability, scalability within scope, teardown, archive, and lawful handoff compatibility.

**65.4.5 Stack Separation Review.** Architecture Review shall verify public-good stack and enterprise stack separation. Foundry architecture shall not place enterprise execution, procurement decisions, finance decisions, public authority decisions, deployment decisions, consent decisions, or operational command functions inside default Foundry objects.

**65.4.6 National and Sovereign Architecture Review.** Where national data, public authority-sensitive work, sovereign compute, National Nodes, National Dense Nexus Cores, or National Portfolio objects are involved, Architecture Review shall verify national routing, data residency, sovereign compute requirements, national support, localization, and national ownership before local delivery.

**65.4.7 Architecture Review Boundary.** Architecture Review completion, architecture fit, reference architecture conformance, design acceptance, or architecture board clearance shall not create certification, public authority approval, procurement status, financeability, maturity status, consent, deployment authorization, operational command, or execution authority.

**65.4.8 Architecture Review Correction.** Architecture Review Records shall be corrected where architecture introduces role collapse, hidden execution, provider lock-in, national bypass, data leakage, Studio deployment implication, Marketplace endorsement implication, Registry approval implication, or handoff overclaim.

**65.4.9 Architecture Review Formula.** Architecture Review shall follow the formula: **review system design against Nexus architecture; preserve planes, roles, stacks, and national routing; block hidden execution; correct architectural drift; never let architecture approval become deployment, procurement, finance, consent, or execution authority.**

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### 65.5 Ontology and Schema Review

**65.5.1 Ontology and Schema Review Identity.** **Ontology and Schema Review** shall be the governed review of controlled vocabulary, ontologies, data dictionaries, metadata models, evidence schemas, proof schemas, public-safe label schemas, Marketplace metadata, Registry state metadata, Studio runtime metadata, readiness schemas, safeguard schemas, support schemas, correction schemas, archive schemas, local extensions, translations, and semantic mappings used in Foundry.

**65.5.2 Ontology and Schema Review Purpose.** Ontology and Schema Review shall preserve semantic integrity, interoperability, public-safe meaning, national localization, local extension compatibility, correctionability, and status truth. It shall prevent schema fields, labels, status terms, dashboard categories, Marketplace categories, Registry states, Studio states, TRL-related fields, readiness fields, public authority fields, finance fields, procurement fields, consent fields, and deployment fields from creating silent authority.

**65.5.3 Ontology and Schema Review Record.** Each Ontology and Schema Review shall have a review record identifying schema or ontology asset, proposed change, affected object classes, controlled vocabulary dependencies, authority-sensitive terms, localization implications, translation implications, validation rules, migration needs, compatibility impacts, reviewer, conflicts, accepted changes, rejected changes, required corrections, deprecation rule, archive rule, and prohibited interpretations.

**65.5.4 Semantic Review Criteria.** Review shall assess clarity, necessity, non-duplication, controlled vocabulary alignment, compatibility, machine-readability, human readability, translation resilience, public-safe meaning, status meaning, authority-sensitive language, local extension risks, migration risk, and downstream interpretation risk.

**65.5.5 Authority-Sensitive Term Review.** Terms relating to approval, certification, recognition, maturity, TRL 1–10, readiness, finance, insurance, donor relevance, public finance, procurement, public authority, consent, deployment, execution, support, warranty, public warning, rating, or validation shall receive heightened review.

**65.5.6 Local Extension Review.** National, regional, sectoral, institutional, or community-specific schema extensions shall preserve canonical identifiers, lineage, controlled vocabulary, no-conversion language, correction links, support status, and archive links. Localization shall not silently fork meaning.

**65.5.7 Ontology and Schema Review Boundary.** Ontology approval, schema conformance, validation success, metadata completeness, or controlled vocabulary update shall not create factual truth, legal sufficiency, certification, public authority approval, procurement status, financeability, consent, deployment authorization, or execution authority.

**65.5.8 Ontology and Schema Review Correction.** Review Records shall be corrected where terms drift, validation implies authority, translations alter meaning, local extensions fork the rail, Registry states mislead, Marketplace metadata overclaims, Studio metadata implies deployment, or schema review is treated as approval.

**65.5.9 Ontology and Schema Review Formula.** Ontology and Schema Review shall follow the formula: **govern meaning before automation; control authority-sensitive terms; preserve semantic lineage; localize without forking; correct semantic drift; never let schema validity become approval, certification, finance, procurement, consent, deployment, or execution.**

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### 65.6 Data Review

**65.6.1 Data Review Identity.** **Data Review** shall be the governed review of data sources, datasets, metadata, data dictionaries, provenance, custody, classification, sensitivity, residency, access, retention, deletion, sealing, cross-border transfer, data-room use, secure-room use, compute-to-data use, AI use, output review, public-safe summaries, protected knowledge, Indigenous-sensitive knowledge where applicable, community-sensitive information, health-sensitive information, infrastructure-sensitive information, cyber-sensitive information, and public authority-sensitive information.

**65.6.2 Data Review Purpose.** Data Review shall ensure that Foundry data work is lawful, bounded, classified, safeguarded, access-controlled, purpose-bound, output-reviewed, correctionable, and nationally routed where required. It shall prevent data availability, technical access, or contributor possession from being treated as permission.

**65.6.3 Data Review Record.** Each Data Review shall have a Data Review Record identifying data source, steward or custodian, data class, sensitivity class, provenance, consent or permission status where applicable, residency, access rules, permitted uses, prohibited uses, AI-use conditions, data-room requirements, secure-room requirements, output-review requirements, retention rule, deletion or sealing rule, cross-border transfer rule, reviewer, findings, required corrections, archive rule, and prohibited interpretations.

**65.6.4 Data Classification Review.** Data Review shall classify data as public-safe, controlled, restricted, confidential, national-only, sovereign-sensitive, public authority-sensitive, community-sensitive, Indigenous-sensitive where applicable, protected knowledge, health-sensitive, infrastructure-sensitive, cyber-sensitive, legal-sensitive, or archive-only as appropriate. Classification shall control access and output.

**65.6.5 AI and Data Use Review.** Data Review shall identify whether data may be used for AI retrieval, embedding, summarization, translation, classification, training, fine-tuning, agent workflows, or output generation. AI use shall be prohibited unless explicitly permitted by the Data Review Record.

**65.6.6 Output Review.** Data Review shall define review for outputs derived from restricted, sensitive, protected, or national data. Derived outputs, aggregates, embeddings, transformed datasets, dashboard extracts, screenshots, and public-safe summaries shall not escape classification without review.

**65.6.7 Data Review Boundary.** Data Review completion, data classification, metadata completion, data-room access, secure-room access, output review, or data-quality note shall not create data ownership, unrestricted use rights, publication permission, AI training permission, public authority approval, procurement status, financeability, consent, deployment authorization, or execution authority.

**65.6.8 Data Review Correction.** Data Review Records shall be corrected where classification is wrong, permissions change, data sensitivity changes, residency is missed, AI use exceeds scope, outputs escape review, protected knowledge is exposed, Indigenous protocols are missed where applicable, or Data Review is treated as permission.

**65.6.9 Data Review Formula.** Data Review shall follow the formula: **classify before use; identify custody and permission; restrict access and AI use; review outputs; correct data drift; never let data review become data ownership, consent, deployment, or execution authority.**

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### 65.7 Cyber Review

**65.7.1 Cyber Review Identity.** **Cyber Review** shall be the governed review of cybersecurity risks, controls, configurations, identities, access, privileged access, secrets, keys, certificates, vulnerabilities, dependencies, network exposure, egress, logging where appropriate, monitoring where appropriate, incident pathways, secure rooms, data rooms, connectors, APIs, agents, dashboards, Studio runtimes, Marketplace surfaces, Registry surfaces, infrastructure templates, Golden Images, cloud environments, sovereign compute, edge environments, observability systems, and teardown.

**65.7.2 Cyber Review Purpose.** Cyber Review shall reduce cyber risk within recorded scope and identify required controls before release, Marketplace listing, Registry status, Studio runtime, public demonstration, Core Build use, Nexus Universe use, data-room use, secure-room use, public authority learning, readiness mapping, support, or handoff preparation. It shall not create cybersecurity certification.

**65.7.3 Cyber Review Record.** Each Cyber Review shall have a Cyber Review Record identifying object, version, environment, threat model where appropriate, data class, access class, controls reviewed, tests performed, vulnerabilities found, severity, remediation status, residual risk, support status, reviewer, conflicts, correction pathway, public-safe disclosure limits, archive rule, and prohibited interpretations.

**65.7.4 Cyber Review Criteria.** Cyber Review shall assess identity and access management, privileged access, secrets management, key and certificate control, secure configuration, dependency vulnerabilities, API exposure, connector security, egress controls, input validation, output validation, logging where appropriate, monitoring where appropriate, incident response, secure-room controls, data-room controls, AI tool controls, and teardown closure.

**65.7.5 Authorized Testing.** Cyber Review shall occur only within authorized scope. It shall not authorize uncontrolled penetration testing, exploit deployment, credential probing, data exfiltration, public vulnerability disclosure, live-system attack, or testing against third-party systems outside recorded authorization.

**65.7.6 Cyber Review and Public Disclosure.** Cyber findings shall be access-controlled where disclosure could create risk. Public-safe reporting may describe controls and corrections in aggregate or bounded language without exposing exploitable details.

**65.7.7 Cyber Review Boundary.** Cyber Review completion, vulnerability scan, hardening record, remediation proof, secure-room review, or security finding closure shall not create cybersecurity certification, legal compliance certification, public authority approval, procurement status, financeability, insurability, consent, deployment authorization, operational readiness, or execution authority.

**65.7.8 Cyber Review Correction.** Cyber Review Records shall be corrected where scope is misstated, vulnerabilities are hidden, remediation is overstated, support changes, dependencies become vulnerable, access expands, secrets are exposed, or Cyber Review is treated as certification or deployment approval.

**65.7.9 Cyber Review Formula.** Cyber Review shall follow the formula: **review security within authorized scope; protect sensitive findings; remediate and record residual risk; restrict unsafe objects; correct cyber drift; never let cyber review become cybersecurity certification, procurement, finance, consent, deployment, or execution.**

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### 65.8 AI Review

**65.8.1 AI Review Identity.** **AI Review** shall be the governed review of AI models, AI systems, agentic workflows, model cards, system cards, agent records, tool permissions, retrieval scope, memory rules, prompt or workflow templates, logging rules where appropriate, evaluation harnesses, red-team findings, automated claim-prevention controls, output-review rules, Studio agents, dashboard agents, Marketplace agents, Registry agents, support agents, and AI-assisted evidence or publication workflows.

**65.8.2 AI Review Purpose.** AI Review shall ensure that AI and agentic systems used by Foundry are purpose-bounded, data-bounded, tool-bounded, human-review-bounded, public-safe, safeguard-aware, cyber-aware, support-aware, correctionable, and capable of shutdown. It shall prevent hidden automation, hallucinated authority, unauthorized data use, unsafe memory, prompt injection, tool overreach, unsupported claims, public authority confusion, finance or procurement overclaim, consent inference, deployment implication, and execution by agentic workflow.

**65.8.3 AI Review Record.** Each AI Review shall have an AI Review Record identifying model, system, agent, workflow, purpose, provider dependency, model version or versioning rule, data classes, retrieval scope, memory rule, tool permissions, autonomy level, human approval points, evaluation results, red-team results, public-safe controls, safeguard controls, cyber controls, support status, shutdown triggers, reviewer, findings, required corrections, archive rule, and prohibited interpretations.

**65.8.4 AI Review Criteria.** AI Review shall assess model suitability within scope, data permissions, retrieval boundaries, memory behavior, tool permissions, prompt injection resilience, hallucination risk, bias or harm concerns where relevant, public-safe claim risk, authority-overclaim prevention, human review adequacy, logging appropriateness, explainability needs, support burden, and shutdown conditions.

**65.8.5 Agentic Workflow Review.** Agentic workflows shall receive heightened review where agents can access tools, write records, update metadata, interact with users, access restricted data, call external systems, generate public materials, summarize public authority materials, summarize finance-readable materials, or prepare handoff packages.

**65.8.6 AI Output Review.** AI output shall be labeled as draft, review-support, analysis-support, restricted, public-safe candidate, or reviewed output as applicable. AI output shall not update Registry status, publish Marketplace listings, activate Studio runtime, issue public communications, infer consent, approve readiness, or trigger handoff without human review and competent record.

**65.8.7 AI Review Boundary.** AI Review completion, model-card acceptance, system-card acceptance, agent evaluation, red-team result, Studio activation, or successful AI workflow shall not certify AI safety, authorize sensitive data use, create public authority approval, procurement status, financeability, consent, deployment authorization, operational command, or execution authority.

**65.8.8 AI Review Correction.** AI Review Records shall be corrected where models change, agents overreach, tool permissions expand, data access exceeds scope, memory rules fail, red-team findings are hidden, automated claim-prevention fails, AI outputs overclaim, or AI Review is treated as certification.

**65.8.9 AI Review Formula.** AI Review shall follow the formula: **register and bound AI systems; restrict data and tools; evaluate and red-team; require human review for authority-sensitive meaning; shut down on drift; never let AI review become AI certification, consent, deployment, or execution authority.**

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### 65.9 Dual-Use Review

**65.9.1 Dual-Use Review Identity.** **Dual-Use Review** shall be the governed review of Foundry objects, data, models, agents, code, infrastructure templates, dashboards, observability outputs, geospatial layers, cyber materials, AI workflows, sensor integrations, secure-room materials, public-safe reports, Studio runtimes, Marketplace listings, Registry records, National Portfolio materials, Core Build outputs, Nexus Universe outputs, and handoff packages that may create both beneficial public-good uses and harmful, unsafe, abusive, coercive, surveillance, cyber, biological, physical, infrastructure, geopolitical, security, or rights-impacting uses.

**65.9.2 Dual-Use Review Purpose.** Dual-Use Review shall prevent Foundry from publishing, releasing, listing, registering, demonstrating, or routing materials in ways that enable misuse, expose sensitive capabilities, increase harm, support unauthorized surveillance, facilitate cyber abuse, undermine safeguards, expose protected knowledge, or create operational capability beyond public-good purpose.

**65.9.3 Dual-Use Review Record.** Each Dual-Use Review shall have a Dual-Use Review Record identifying object, capability, beneficial use, potential misuse, affected actors, sensitivity class, data class, AI class, cyber class, geospatial class, infrastructure sensitivity, publication risk, access controls, output controls, release restrictions, reviewer, findings, required mitigations, correction pathway, archive rule, and prohibited interpretations.

**65.9.4 Dual-Use Triggers.** Dual-Use Review shall be triggered by materials involving cyber techniques, agentic automation, sensitive geospatial visibility, critical infrastructure, autonomous systems, drones, robotics, biosecurity-relevant analysis, health-sensitive systems, energy systems, public safety systems, degraded-mode operations, sensor networks, surveillance-adjacent capabilities, exploitability, operational control, or instructions that could materially enable harm.

**65.9.5 Mitigation Measures.** Dual-Use mitigation may include access restriction, redaction, aggregation, delay, synthetic data substitution, controlled release, secure-room use, no-download use, compute-to-data use, public-safe summary, removal of operational details, tool-permission restriction, agent shutdown, Marketplace restriction, Registry restriction, Studio restriction, Core Build restriction, Nexus Universe material revision, handoff limitation, or archive.

**65.9.6 Dual-Use and Public-Safe Release.** Public-safe release shall not expose operationally sensitive details, exploit paths, sensitive coordinates, system vulnerabilities, restricted workflows, or instructions that could enable harm. Public-good transparency shall be balanced with safety.

**65.9.7 Dual-Use Review Boundary.** Dual-Use Review completion, mitigation, restriction, or public-safe release shall not create legal compliance certification, public authority approval, security clearance, procurement status, financeability, consent, deployment authorization, operational command, or execution authority.

**65.9.8 Dual-Use Review Correction.** Dual-Use Review Records shall be corrected where misuse risks are missed, public materials expose sensitive capability, access controls fail, Studio runtimes expose operational details, Marketplace listing enables misuse, Registry record reveals too much, or Dual-Use Review is treated as approval for deployment.

**65.9.9 Dual-Use Review Formula.** Dual-Use Review shall follow the formula: **identify beneficial use and misuse pathways; restrict operationally sensitive detail; publish only public-safely; correct exposure; never let dual-use review become security approval, public authority approval, consent, deployment, or execution.**

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### 65.10 Public-Safe Review

**65.10.1 Public-Safe Review Identity.** **Public-Safe Review** shall be the governed review of materials, dashboards, reports, summaries, Marketplace descriptions, Registry descriptions, Studio explanations, Academy materials, National Portfolio summaries, public authority learning materials, Nexus Universe materials, Core Build materials, public notices, correction notices, withdrawal notices, archive notices, media materials, and public-facing or controlled-public statements before release to their intended audience.

**65.10.2 Public-Safe Review Purpose.** Public-Safe Review shall ensure that communication is accurate, source-grounded, accessible, claims-safe, audience-appropriate, safeguard-aware, public authority-boundary-compliant, finance-boundary-compliant, procurement-neutral, consent-boundary-compliant, provider-neutral, sponsor-neutral, correctionable, and not likely to create unsafe public meaning.

**65.10.3 Public-Safe Review Record.** Each Public-Safe Review shall have a Public-Safe Review Record identifying material, audience, channel, source records, public-safe class, sensitivity class, claims reviewed, labels required, boundary language required, accessibility review, translation review where applicable, media risk, reviewer, findings, required revisions, release limits, correction pathway, archive rule, and prohibited interpretations.

**65.10.4 Public-Safe Review Criteria.** Public-Safe Review shall assess unsupported claims, excessive certainty, public warning implication, rating implication, official classification implication, public authority overclaim, finance or procurement overclaim, maturity overclaim, provider endorsement, sponsor control implication, consent implication, deployment implication, operational command language, community harm, Indigenous protocol sensitivity where applicable, accessibility, and translation meaning.

**65.10.5 Audience-Specific Review.** Public-safe meaning shall be reviewed against audience. Internal technical notes, controlled-public summaries, public reports, media-facing text, capital-reader materials, public authority learning materials, community materials, Marketplace descriptions, Registry descriptions, Studio instructions, and Nexus Universe scripts shall not be treated as interchangeable.

**65.10.6 Visual and Dashboard Review.** Public-Safe Review shall include review of visual elements where relevant, including charts, maps, colors, icons, rankings, thresholds, confidence labels, uncertainty labels, drift labels, legends, screenshots, public links, exports, and dashboard embeds.

**65.10.7 Public-Safe Review Boundary.** Public-Safe Review completion, public-safe release, approved communication, public report, dashboard label, Marketplace description, Registry description, or Studio explanation shall not create public warning, official classification, certification, procurement status, financeability, public authority approval, consent, deployment authorization, or execution authority.

**65.10.8 Public-Safe Review Correction.** Public-Safe Review Records shall be corrected where language misleads, translations weaken boundaries, visuals overclaim, labels are omitted, source records change, public authority meaning is overstated, finance or procurement meaning is overstated, or public-safe review is treated as official status.

**65.10.9 Public-Safe Review Formula.** Public-Safe Review shall follow the formula: **review public meaning before release; align language with records; make limits visible; adapt to audience; correct misleading communication; never let safe communication become warning, approval, certification, finance, procurement, consent, deployment, or execution.**

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### 65.11 Public Authority Boundary Review

**65.11.1 Public Authority Boundary Review Identity.** **Public Authority Boundary Review** shall be the governed review of any Foundry object, material, dashboard, Studio runtime, public-safe report, National Portfolio item, readiness map, Observatory output, DRI output, GRIx context, public authority learning material, Core Build output, Nexus Universe output, Marketplace listing, Registry record, or handoff package that involves, refers to, is intended for, may be read by, or may be used in proximity to public authorities.

**65.11.2 Public Authority Boundary Review Purpose.** Public Authority Boundary Review shall preserve public authority learning without public authority substitution. It shall prevent Foundry from being misrepresented as regulator, public authority, public warning body, emergency command center, policy decision-maker, procurement body, public finance allocator, compliance certifier, official risk classifier, licensing body, permitting body, enforcement body, or public authority agent.

**65.11.3 Public Authority Boundary Review Record.** Each review shall have a Public Authority Boundary Review Record identifying public authority context, jurisdiction, material or object, intended use, source records, public authority sensitivity, boundary language, decision-risk, warning-risk, procurement-risk, public finance-risk, regulatory-risk, emergency-command-risk, reviewer, findings, required revisions, release limits, correction pathway, archive rule, and prohibited interpretations.

**65.11.4 Review Criteria.** Review shall assess whether materials imply public authority approval, official warning, official classification, regulatory comfort, compliance finding, procurement action, public finance allocation, policy adoption, emergency command, operational control, surveillance authority, enforcement action, or legal decision. Ambiguous language shall be revised or restricted.

**65.11.5 Public Authority Participation Language.** References to public authority attendance, feedback, questions, workshop participation, learning session participation, data review, dashboard viewing, Studio participation, Nexus Universe attendance, National Portfolio discussion, or Core Build observation shall be carefully bounded. Participation shall not be described as approval or adoption.

**65.11.6 Public Authority Learning Materials.** Public authority learning materials shall state learning purpose, non-decision status, no public authority substitution, no reliance as official approval, no procurement effect, no public finance effect, no emergency command effect, and correction pathway where appropriate.

**65.11.7 Public Authority Boundary Review Boundary.** Completion of Public Authority Boundary Review shall not create public authority approval, official classification, regulatory comfort, procurement status, public finance allocation, policy endorsement, compliance determination, consent, deployment authorization, emergency command, or execution authority.

**65.11.8 Public Authority Boundary Review Correction.** Records and materials shall be corrected where public authority presence is overclaimed, learning is treated as approval, dashboards are used as official classification, public-safe reports are treated as warnings, or handoff packages imply public authority authorization.

**65.11.9 Public Authority Boundary Review Formula.** Public Authority Boundary Review shall follow the formula: **separate learning from authority; label public authority participation accurately; block official-status implication; correct public authority overclaim; never let public authority interaction become public authority action by implication.**

***

### 65.12 Finance Boundary Review

**65.12.1 Finance Boundary Review Identity.** **Finance Boundary Review** shall be the governed review of Foundry objects, readiness mappings, finance-readable materials, capital-reader rooms, investor council inputs, insurance-reader materials, donor and public finance relevance materials, National Portfolio materials, GRA-supported materials, Deployment Units, handoff dependency packages, Marketplace descriptions, Registry records, Studio runtimes, Nexus Universe materials, Core Build materials, and public-safe reports that may be read as finance, investment, insurance, underwriting, donor, public finance, bankability, valuation, transaction, or solicitation signals.

**65.12.2 Finance Boundary Review Purpose.** Finance Boundary Review shall preserve finance-readiness without finance execution. It shall prevent Foundry from being misrepresented as fund, broker, dealer, investment adviser, underwriter, lender, insurer, reinsurer, guarantee provider, rating agency, donor allocator, public finance allocator, securities platform, transaction room, financial promoter, or project finance arranger.

**65.12.3 Finance Boundary Review Record.** Each review shall have a Finance Boundary Review Record identifying material or object, intended audience, finance-sensitive terms, capital-reader context, insurance-reader context, donor/public finance context, readiness claims, no-reliance language, regulated-perimeter controls, confidentiality controls, competition controls, reviewer, findings, required revisions, release limits, correction pathway, archive rule, and prohibited interpretations.

**65.12.4 No-Reliance Controls.** Finance-facing or finance-adjacent materials shall include no-reliance, non-advisory, non-soliciting, non-transactional, non-underwriting, non-commitment, non-rating, non-valuation, competition-compliant, confidentiality-aware, and regulated-perimeter language as appropriate to audience and risk.

**65.12.5 Prohibited Finance Conversions.** Review shall block conversion of readiness mapping into financeability, bankability, investability, insurability, underwriting acceptance, donor approval, public finance approval, guarantee eligibility, transaction readiness, valuation, investment recommendation, insurance recommendation, or capital commitment.

**65.12.6 Capital-Reader Participation Language.** Capital-reader, insurer, donor, public finance actor, investor council, or enterprise actor participation shall be described as reading, learning, feedback, diligence-question formation, dependency review, or no-reliance review only where accurate. Presence shall not be described as investment interest, underwriting interest, donor interest, public finance interest, or approval.

**65.12.7 Finance Boundary Review Boundary.** Completion of Finance Boundary Review shall not create financeability, bankability, investability, insurability, underwriting acceptance, donor approval, public finance approval, investment advice, securities compliance, valuation, transaction readiness, procurement status, public authority approval, consent, deployment authorization, or execution authority.

**65.12.8 Finance Boundary Review Correction.** Records and materials shall be corrected where finance language overclaims, no-reliance language is missing, capital-reader presence is overstated, insurance relevance is treated as insurability, donor relevance is treated as donor approval, public finance relevance is treated as public finance allocation, or readiness language becomes transaction signal.

**65.12.9 Finance Boundary Review Formula.** Finance Boundary Review shall follow the formula: **make dependencies readable without creating reliance; apply no-reliance and regulated-perimeter controls; prevent finance and insurance overclaim; correct transaction implication; never let readiness become finance, insurance, investment, donor, public finance, consent, deployment, or execution.**

***

### 65.13 Procurement Neutrality Review

**65.13.1 Procurement Neutrality Review Identity.** **Procurement Neutrality Review** shall be the governed review of Foundry objects, Marketplace listings, Registry records, Studio runtimes, Reference Implementations, Benchmarks, Provider Contributions, National Portfolio materials, public authority learning materials, readiness materials, Deployment Units, Core Build outputs, Nexus Universe materials, public-safe reports, and handoff packages that could be interpreted as procurement recommendation, prequalification, preferred vendor status, technical specification, shortlisting, scoring, evaluation, or purchasing guidance.

**65.13.2 Procurement Neutrality Review Purpose.** Procurement Neutrality Review shall preserve Foundry as public-good production and learning infrastructure, not a procurement body. It shall prevent Marketplace visibility, Registry presence, Studio demonstration, provider contribution, benchmark result, Core Build use, Nexus Universe visibility, National Portfolio inclusion, public authority participation, or readiness mapping from becoming procurement implication.

**65.13.3 Procurement Neutrality Review Record.** Each review shall have a Procurement Neutrality Review Record identifying material or object, procurement-sensitive audience, provider dependencies, sponsor involvement, benchmark involvement, Marketplace status, Registry status, Studio status, public authority context, no-preferred-vendor language, reviewer, findings, required revisions, release limits, correction pathway, archive rule, and prohibited interpretations.

**65.13.4 Review Criteria.** Review shall assess whether language, rankings, categories, featured placement, comparison tables, benchmark visuals, provider acknowledgements, reference implementations, technical requirements, deployment units, or public authority materials imply preferred vendor, approved supplier, procurement-ready object, certified technology, compliant solution, procurement shortlist, procurement score, or tender specification.

**65.13.5 Provider and Sponsor Controls.** Provider or sponsor participation shall be disclosed where material and shall not control procurement-sensitive wording, Marketplace placement, benchmark presentation, public authority learning materials, National Portfolio materials, or readiness materials.

**65.13.6 Reference Implementation Review.** Reference Implementations shall clearly distinguish mandatory public-good baseline requirements from example provider choices. Example provider choices shall not be framed as procurement specification or required supplier.

**65.13.7 Procurement Neutrality Review Boundary.** Completion of Procurement Neutrality Review shall not create procurement compliance, procurement eligibility, vendor approval, technical prequalification, public authority approval, financeability, consent, deployment authorization, or execution authority.

**65.13.8 Procurement Neutrality Review Correction.** Records and materials shall be corrected where provider preference is implied, benchmark results are used as procurement evidence, Marketplace ranking implies recommendation, Registry presence implies approval, Studio demonstration implies readiness, or National Portfolio inclusion implies government procurement priority.

**65.13.9 Procurement Neutrality Review Formula.** Procurement Neutrality Review shall follow the formula: **identify procurement-sensitive meaning; remove preferred-vendor implication; separate examples from specifications; disclose provider influence; correct procurement overclaim; never let Foundry output become procurement recommendation or vendor approval.**

***

### 65.14 Community Safeguard Review

**65.14.1 Community Safeguard Review Identity.** **Community Safeguard Review** shall be the governed review of Foundry objects, data, dashboards, Observatory outputs, public-safe reports, National Portfolio materials, Studio runtimes, Marketplace materials, Registry records, readiness mappings, Core Build outputs, Nexus Universe materials, and handoff packages that involve, affect, represent, collect information from, visualize, describe, or could materially impact communities, affected stakeholders, civil society, public-interest actors, youth, local institutions, vulnerable populations, place-based groups, or community-sensitive contexts.

**65.14.2 Community Safeguard Review Purpose.** Community Safeguard Review shall ensure that Foundry work does not extract community knowledge, expose vulnerability, stigmatize communities, imply consent, misrepresent participation, create unsafe public meaning, enable harm, bypass local context, or use community presence as decorative legitimacy. It shall preserve non-extractive participation and public-good legitimacy.

**65.14.3 Community Safeguard Review Record.** Each review shall have a Community Safeguard Review Record identifying affected community or context where safe and appropriate, material or object, data classes, geospatial sensitivity, vulnerability sensitivity, participation history, consent status if separately recorded, attribution restrictions, public-safe needs, language needs, accessibility needs, safeguard conditions, reviewer, findings, required controls, correction pathway, archive rule, and prohibited interpretations.

**65.14.4 Review Criteria.** Review shall assess whether materials expose sensitive places, vulnerabilities, identities, local risk knowledge, community-sensitive data, protected knowledge, or implementation concerns; whether participation is overstated; whether consent is implied; whether language is stigmatizing; whether public-safe reporting could create harm; whether access or publication should be restricted; and whether local context has been preserved.

**65.14.5 Participation Without Consent.** Community participation, feedback, data contribution, dashboard viewing, Studio interaction, Nexus Universe attendance, public authority learning participation, National Portfolio discussion, or public-safe review shall not be treated as consent, social license, endorsement, rights waiver, deployment approval, or execution authorization unless separately and lawfully recorded.

**65.14.6 Non-Extractive Use.** Community Safeguard Review shall assess whether knowledge is being used within the restrictions under which it was shared, whether attribution is appropriate, whether anonymity or aggregation is required, whether public-safe summaries are sufficient, and whether withdrawal or correction pathways are available.

**65.14.7 Community Safeguard Review Boundary.** Completion of Community Safeguard Review shall not create community consent, social license, legal compliance certification, public authority approval, procurement status, financeability, deployment authorization, or execution authority. It creates safeguard conditions and limits.

**65.14.8 Community Safeguard Review Correction.** Records and materials shall be corrected, restricted, withdrawn, sealed, or archived where community context is misrepresented, participation is overclaimed, sensitive information is exposed, public-safe language harms, consent is implied, or community materials are used to justify deployment.

**65.14.9 Community Safeguard Review Formula.** Community Safeguard Review shall follow the formula: **identify affected communities and contexts; prevent extraction and stigma; protect sensitive knowledge; preserve participation without consent; correct harm; never let community review become consent, approval, deployment, or execution.**

***

### 65.15 Indigenous Protocol Review Where Applicable

**65.15.1 Indigenous Protocol Review Identity.** **Indigenous Protocol Review Where Applicable** shall be the governed review of Foundry objects, data, dashboards, observability outputs, geospatial layers, public-safe reports, National Portfolio materials, Studio runtimes, Marketplace materials, Registry records, readiness mappings, Core Build outputs, Nexus Universe materials, public authority learning materials, and handoff packages that involve, affect, represent, collect information from, visualize, describe, or may materially impact Indigenous peoples, Indigenous institutions, Tribal or First Nations bodies, Indigenous lands, Indigenous data, Indigenous knowledge, protected knowledge, sacred or culturally sensitive places, or Indigenous rights and governance contexts.

**65.15.2 Indigenous Protocol Review Purpose.** Indigenous Protocol Review shall ensure that Foundry respects Indigenous protocols, governance, data sovereignty, protected knowledge, attribution limits, consent boundaries, place sensitivity, cultural sensitivity, community-defined restrictions, and lawful engagement pathways where applicable. It shall prevent extraction, tokenization, protected knowledge exposure, consent overclaim, and public-good misuse.

**65.15.3 Indigenous Protocol Review Record.** Each review shall have an Indigenous Protocol Review Record identifying Indigenous context where safe and appropriate, relevant institution or protocol pathway where recorded, material or object, data class, protected knowledge status, place sensitivity, participation history, permission or consent status if separately recorded, attribution restrictions, access restrictions, public-safe conditions, national routing, reviewer or protocol steward where applicable, findings, required controls, correction pathway, archive rule, and prohibited interpretations.

**65.15.4 Review Criteria.** Review shall assess whether Indigenous knowledge, protected knowledge, data, geospatial layers, cultural materials, sacred places, traditional knowledge, community-defined restrictions, or rights-sensitive information are involved; whether appropriate protocols apply; whether consent has been separately recorded where required; whether attribution is permitted; whether publication is restricted; whether summaries must be controlled; and whether use should pause or cease.

**65.15.5 Consent and Permission Discipline.** Indigenous participation, attendance, contribution, feedback, data sharing, dashboard viewing, Studio interaction, Nexus Universe participation, National Portfolio discussion, public authority learning participation, or public-safe review shall not create Indigenous consent, protected knowledge permission, rights waiver, social license, deployment approval, or execution authorization unless separately and lawfully recorded through the appropriate pathway.

**65.15.6 Protected Knowledge Controls.** Indigenous Protocol Review may require non-public treatment, aggregation, masking, redaction, secure-room controls, no-download access, attribution removal, publication restriction, output review, withdrawal, sealing, archive restriction, or deletion where required.

**65.15.7 Indigenous Protocol Review Boundary.** Completion of Indigenous Protocol Review shall not create Indigenous consent, legal compliance certification, public authority approval, procurement status, financeability, deployment authorization, or execution authority. It creates conditions, restrictions, corrections, or non-continuation pathways.

**65.15.8 Indigenous Protocol Review Correction.** Records and materials shall be corrected, restricted, withdrawn, sealed, deleted where required, or archived where Indigenous protocols are missed, protected knowledge is exposed, consent is implied without record, place sensitivity is mishandled, attribution is wrong, or materials are used to justify deployment.

**65.15.9 Indigenous Protocol Review Formula.** Indigenous Protocol Review shall follow the formula: **identify Indigenous relevance early; follow applicable protocols; protect knowledge and place sensitivity; preserve consent boundaries; restrict or withdraw where required; never let participation become consent, approval, deployment, or execution.**

***

### 65.16 Legal and Jurisdictional Review

**65.16.1 Legal and Jurisdictional Review Identity.** **Legal and Jurisdictional Review** shall be the governed review of legal, jurisdictional, institutional, cross-border, data, privacy, cyber, AI, intellectual property, licensing, accessibility, public authority, procurement, finance, insurance, donor, public finance, community, Indigenous protocol, employment, contractor, competition, export, sanctions, liability, reliance, public-safe publication, and lawful handoff issues affecting Foundry work.

**65.16.2 Legal and Jurisdictional Review Purpose.** Legal and Jurisdictional Review shall identify legal and jurisdictional dependencies, restrictions, role boundaries, records, and external counsel needs where appropriate. It shall prevent Foundry from unintentionally becoming a regulator, certifier, procurement body, financial actor, insurer, broker, legal adviser, public authority agent, employer, contractor engager, deployment authority, or execution actor by default.

**65.16.3 Legal and Jurisdictional Review Record.** Each review shall have a Legal and Jurisdictional Review Record identifying object or material, jurisdictions involved, legal issue classes, role boundaries, data and privacy issues, cyber issues, AI issues, IP and license issues, public authority issues, procurement issues, finance or insurance issues, community or Indigenous issues where applicable, employment or contractor implications, competition issues, reliance limits, required counsel or external review if any, findings, required corrections, archive rule, and prohibited interpretations.

**65.16.4 Jurisdictional Triggers.** Review shall be triggered by cross-border data movement, national data, public authority-sensitive materials, regulated-sector relevance, public-facing claims, finance-readable materials, procurement-sensitive materials, insurance-readable materials, provider contracts, sponsor arrangements, licensing terms, contributor status, employment-like arrangements, Indigenous protocol relevance where applicable, protected knowledge, export-sensitive technology, sanctions-sensitive actors, and lawful handoff proximity.

**65.16.5 Legal Boundary Language.** Materials subject to legal or jurisdictional sensitivity shall include appropriate no-legal-advice, no-reliance, no-certification, no-public-authority-substitution, no-procurement-effect, no-finance-effect, no-consent-effect, no-deployment-authorization, and no-execution-authority language where applicable.

**65.16.6 Counsel and Competent Authority Escalation.** Where legal questions exceed Foundry review competence, Legal and Jurisdictional Review shall route the matter to appropriate legal counsel, competent institutional authority, public authority, data steward, Indigenous protocol pathway where applicable, or lawful downstream actor. Foundry shall not resolve external legal authority questions by implication.

**65.16.7 Legal and Jurisdictional Review Boundary.** Completion of Legal and Jurisdictional Review shall not create legal advice, legal compliance certification, public authority approval, procurement status, financeability, insurability, consent, deployment authorization, operational command, or execution authority unless separately and lawfully recorded by competent actors.

**65.16.8 Legal and Jurisdictional Review Correction.** Records and materials shall be corrected where jurisdiction is wrong, legal scope is overstated, no-reliance language is missing, external counsel is required but absent, contributor role is misclassified, cross-border transfer risk is missed, or legal review is treated as compliance certification.

**65.16.9 Legal and Jurisdictional Review Formula.** Legal and Jurisdictional Review shall follow the formula: **identify legal and jurisdictional dependencies; route beyond Foundry where needed; state no-reliance and boundary language; correct legal overclaim; never let legal review become legal advice, compliance certification, deployment authorization, or execution.**

***

### 65.17 Release Review

**65.17.1 Release Review Identity.** **Release Review** shall be the governed review that determines whether a Foundry object may be released within a defined release class, including internal release, restricted release, public-safe release, controlled-public release, Marketplace release, Registry release, Studio release, National Portfolio release, Academy release, support release, correction release, archive release, handoff-dependency release, or non-continuation release.

**65.17.2 Release Review Purpose.** Release Review shall ensure that release occurs only after required records, reviews, tests, support classification, public-safe labels, safeguards, national routing, Registry references, Marketplace metadata, Studio metadata, correction pathways, rollback pathways, and archive conditions are complete for the release class. It shall prevent release from becoming deployment authorization.

**65.17.3 Release Review Record.** Each Release Review shall have a Release Review Record identifying object, version, release class, source records, required prior reviews, review completion status, test status, evidence status, data status, AI status, cyber status, public-safe status, safeguard status, national routing status, support status, documentation status, Registry status, Marketplace status, Studio status, limitations, rollback pathway, correction pathway, archive rule, reviewer, decision, and prohibited interpretations.

**65.17.4 Release Gate Criteria.** Release Review shall verify that required reviews are complete or explicitly non-applicable by record; limitations are visible; support status is honest; public-safe labels are present; sensitive data is controlled; AI outputs are reviewed; cyber issues are resolved or restricted; safeguards are addressed; national routing is complete where required; Marketplace, Registry, and Studio states are aligned; and no-conversion language is present.

**65.17.5 Conditional Release.** Conditional release shall be permitted only where conditions are recorded, visible to intended users, enforceable, compatible with intended use, and linked to correction or renewal. Conditional release shall not be used to hide blocking risks.

**65.17.6 Release Rollback.** Release Review shall confirm rollback, withdrawal, Registry correction, Marketplace delisting, Studio pause, support status change, public-safe notice, handoff recall, and archive pathways where applicable.

**65.17.7 Release Review Boundary.** Release Review completion, release approval within Foundry, signed release artifact, public-safe release, Marketplace release, Registry release, Studio release, or handoff-dependency release shall not create certification, procurement status, financeability, public authority approval, maturity status, consent, deployment authorization, operational command, or execution authority.

**65.17.8 Release Review Correction.** Release Review Records shall be corrected where required reviews were incomplete, limitations were hidden, support was overstated, public-safe labels were missing, national routing was bypassed, safeguards were incomplete, Registry or Marketplace status diverged, Studio runtime was unsafe, or release was treated as deployment approval.

**65.17.9 Release Review Formula.** Release Review shall follow the formula: **confirm all required reviews and records; release only by class; state limits visibly; preserve rollback; correct release errors; never let release become certification, finance, procurement, consent, deployment, or execution.**

***

### 65.18 Support Review

**65.18.1 Support Review Identity.** **Support Review** shall be the governed review of support scope, support class, maintainer capacity, steward capacity, reviewer capacity, security update capacity, dependency update capacity, documentation support, user support, Studio support, Marketplace support, Registry support, National Portfolio support, handoff support, correction support, end-of-support conditions, and support archive for Foundry objects.

**65.18.2 Support Review Purpose.** Support Review shall ensure that Foundry objects are not released, listed, registered, Studio-activated, publicly presented, nationally routed, or handoff-adjacent without honest understanding of support obligations and limits. Support Review shall prevent availability from being mistaken for maintained status.

**65.18.3 Support Review Record.** Each Support Review shall have a Support Review Record identifying object, support class, support steward, maintainers, support scope, exclusions, response pathway, maintenance cadence where applicable, security update rule, dependency update rule, documentation status, user obligations, warranty or no-warranty terms, reliance limits, escalation pathway, correction pathway, end-of-support condition, archive rule, reviewer, findings, and prohibited interpretations.

**65.18.4 Support Review Criteria.** Support Review shall assess maintainer availability, steward availability, issue pathways, security update capacity, dependency update capacity, documentation quality, user guidance, support queue, support metrics, support risks, public-safe support language, national support capacity, Studio support requirements, Marketplace support display, Registry support state, and archive conditions.

**65.18.5 Support Status Classes.** Support Review may classify objects as unsupported, experimental support, community support, maintainer support, limited support, security-only support, national support, Studio support, Marketplace support, Registry support, handoff support, contracted support where separately agreed, deprecated support, end-of-support, withdrawn, retired, or archived.

**65.18.6 Support Reduction and End-of-Support.** Support Review shall reduce, restrict, or end support where capacity is absent, dependencies are unsupported, vulnerabilities cannot be addressed, documentation is stale, national support is unavailable, Studio support cannot be provided, users misunderstand support, or support burden is inconsistent with public-good value.

**65.18.7 Support Review Boundary.** Support Review completion, support classification, support response, maintenance cadence, security update, dependency update, or support dashboard shall not create warranty, service-level obligation, professional advice, procurement suitability, financeability, public authority approval, consent, deployment authorization, operational command, or execution responsibility unless separately and lawfully contracted.

**65.18.8 Support Review Correction.** Support Review Records shall be corrected where support scope is overstated, exclusions are hidden, dependencies become unsupported, metrics mislead, users misunderstand support, or support review is treated as warranty or deployment approval.

**65.18.9 Support Review Formula.** Support Review shall follow the formula: **classify support before reliance; align support with real capacity; disclose exclusions; reduce support when needed; correct support overclaim; never let support review become warranty, certification, deployment authorization, or execution responsibility.**

***

### 65.19 Archive Review

**65.19.1 Archive Review Identity.** **Archive Review** shall be the governed review that determines whether a Foundry object, Product Line, Rail, Pack, Profile, Schema, Connector, Agent, Dashboard, Evidence Product, Readiness Product, Safeguard Product, Deployment Unit, Marketplace Object, Registry Record, Studio Runtime Package, National Portfolio object, Core Build output, Nexus Universe output, support record, correction record, review record, risk record, BoM, roadmap, release train, public-safe material, or handoff dependency package should be archived, restricted, sealed, deleted where required, retained, reinstated, or marked as non-current.

**65.19.2 Archive Review Purpose.** Archive Review shall preserve institutional memory without preserving current authority. It shall ensure that obsolete, superseded, withdrawn, corrected, unsupported, unsafe, restricted, retired, sunset, or non-continuing objects do not remain visible or usable as current records, current releases, current support, current evidence, current readiness, current handoff basis, current Marketplace listings, current Registry states, or current Studio runtimes.

**65.19.3 Archive Review Record.** Each Archive Review shall have an Archive Review Record identifying object, version, prior status, archive trigger, archive class, source records, release history, support history, correction history, public notice history, Marketplace status, Registry status, Studio status, National Portfolio status, handoff status where applicable, sensitivity class, access restrictions, retention rule, deletion rule, sealing rule where applicable, reinstatement conditions, reviewer, findings, archive decision, and prohibited interpretations.

**65.19.4 Archive Classes.** Archive classes may include public archive, controlled archive, restricted archive, secure archive, national archive, institutional-memory archive, correction archive, support archive, Marketplace archive, Registry archive, Studio archive, Core Build archive, Nexus Universe archive, National Portfolio archive, risk archive, sunsetting archive, sealed archive, deletion-verification archive, and non-continuation archive.

**65.19.5 Archive Access Review.** Archive Review shall classify access according to privacy, data sensitivity, protected knowledge, Indigenous-sensitive knowledge where applicable, community sensitivity, public authority sensitivity, cyber sensitivity, infrastructure sensitivity, health sensitivity, provider confidentiality, sponsor confidentiality, finance-reader materials, procurement-sensitive materials, legal sensitivity, national routing, and public-safe rules.

**65.19.6 Archive Reinstatement Review.** Archived objects may be reinstated only after current review of source validity, dependency status, security status, data permission, AI behavior, public-safe meaning, safeguard conditions, national routing, support capacity, Marketplace status, Registry status, Studio status, readiness status, and intended audience. Reopening a file, relinking a dashboard, copying a repository, or referencing an old report shall not reinstate current status.

**65.19.7 Archive Review Boundary.** Archive Review completion, archive status, deletion verification, sealed status, non-continuation status, or reinstatement review shall not create legal finding, public authority finding, procurement finding, finance conclusion, consent determination, deployment denial, deployment authorization, operational command, or execution effect beyond the archive record.

**65.19.8 Archive Review Correction.** Archive Review Records shall be corrected where archive class is wrong, sensitivity changes, retention rules change, deletion obligations arise, public display overclaims, archived materials are exposed improperly, Marketplace or Registry archive status is wrong, Studio runtime persists, or archived materials are cited as current authority.

**65.19.9 Final Foundry Review Architecture Formula.** The controlling Foundry Review Architecture Formula is that **the Review Matrix assigns risk-based review duties; Evidence Review protects claims and uncertainty; Technical Review protects correctness within specification; Architecture Review protects Nexus structure and stack separation; Ontology and Schema Review protects meaning; Data Review protects data, custody, residency, and output control; Cyber Review protects security within authorized scope; AI Review protects model, agent, tool, and output boundaries; Dual-Use Review protects against harmful capability exposure; Public-Safe Review protects public meaning; Public Authority Boundary Review preserves learning without substitution; Finance Boundary Review preserves readiness without finance execution; Procurement Neutrality Review preserves vendor neutrality and procurement neutrality; Community Safeguard Review protects affected communities without consent overclaim; Indigenous Protocol Review where applicable protects Indigenous protocols, data, knowledge, place, and consent boundaries; Legal and Jurisdictional Review identifies legal dependencies without legal advice or compliance certification; Release Review governs release class without deployment authority; Support Review governs lifecycle support without warranty; and Archive Review preserves memory without current authority. No review matrix assignment, review record, review completion, positive finding, conditional finding, release review, support review, archive review, public-safe clearance, technical clearance, evidence sufficiency note, cyber review, AI review, public authority boundary review, finance boundary review, procurement neutrality review, community safeguard review, Indigenous protocol review, legal review, or correction arising from review creates recognition, certification, accreditation, audit opinion, public authority approval, procurement status, commercial approval, financeability, insurability, maturity certification, consent, deployment authorization, operational command, or execution authority by implication.**

## 66. Testing Architecture

### 66.1 Test Harnesses

**66.1.1 Test Harness Identity.** **Test Harnesses** shall be governed, record-bearing, reproducible where appropriate, support-aware, correctionable, and archive-ready testing environments, scripts, fixtures, workflows, datasets, synthetic datasets, mock services, simulators, evaluators, validators, dashboards, agent sandboxes, connector sandboxes, secure-room test environments, data-room test environments, Studio runtime test environments, public-safe publication test workflows, Marketplace listing test workflows, Registry linkage test workflows, and teardown test workflows used to examine Foundry objects within defined scope.

**66.1.2 Test Harness Purpose.** Test Harnesses shall allow Nexus Foundry to test what it builds before release, publication, Marketplace listing, Registry recording, Studio activation, National Portfolio use, Core Build use, Nexus Universe presentation, public authority learning use, readiness mapping, support classification, correction closure, handoff preparation, or archive. A Test Harness shall make testing repeatable, inspectable, bounded, and correctable; it shall not convert test performance into certification or deployment authorization.

**66.1.3 Test Harness Record.** Each material Test Harness shall have a **Test Harness Record** identifying harness name, purpose, object classes supported, test class, source records, test environment, test data, synthetic data where applicable, mock services, dependencies, tools, permissions, AI involvement where applicable, cyber sensitivity, data sensitivity, public-safe sensitivity, reviewer, expected outputs, limitations, maintenance steward, support status, correction pathway, archive rule, and prohibited interpretations.

**66.1.4 Test Harness Classes.** Test Harness classes may include unit-test harnesses, integration-test harnesses, interoperability-test harnesses, security-test harnesses, performance-test harnesses, simulation-test harnesses, data-quality-test harnesses, AI-output-test harnesses, dashboard-test harnesses, connector-test harnesses, secure-room-test harnesses, public-safe-publication-test harnesses, Marketplace-listing-test harnesses, Studio-runtime-test harnesses, teardown-test harnesses, regression-test harnesses, accessibility-test harnesses, localization-test harnesses, and archive-reinstatement-test harnesses.

**66.1.5 Harness Data Discipline.** Test Harnesses shall use the least sensitive data sufficient for the test. Synthetic, mock, public-safe, aggregate, masked, no-download, secure-room, compute-to-data, or national-only test data shall be used where raw restricted data is not required. Test Harnesses shall not create uncontrolled copies, embeddings, logs, outputs, screenshots, or exports of restricted data.

**66.1.6 Harness Maintenance.** Test Harnesses shall be maintained, versioned, reviewed, and retired where dependencies, schemas, APIs, models, tools, data profiles, security rules, public-safe rules, or support status change. A stale Test Harness shall not be used to support current release claims without review.

**66.1.7 Test Harness Boundary.** Availability, use, successful execution, or passing result of a Test Harness shall not create certification, accreditation, audit opinion, public authority approval, procurement status, financeability, insurability, maturity certification, consent, deployment authorization, operational readiness, or execution authority.

**66.1.8 Test Harness Correction.** Test Harness Records shall be corrected where harness scope is wrong, test data is unsafe, dependencies are stale, outputs are misleading, AI or cyber risk is missed, sensitive logs are retained improperly, or harness results are used as certification or deployment approval.

**66.1.9 Test Harness Formula.** Test Harnesses shall follow the formula: **build bounded test environments; use safe test data; record tools, assumptions, and limits; maintain harnesses as dependencies change; archive stale harnesses; never let harness success become certification, maturity, procurement, finance, consent, deployment, or execution.**

***

### 66.2 Unit Tests

**66.2.1 Unit Test Identity.** **Unit Tests** shall be bounded tests of individual components, functions, modules, schemas, validation rules, connectors, transformation scripts, AI-control functions, dashboard components, documentation generators, publication checks, support checks, teardown scripts, or other discrete Foundry units against recorded expected behavior.

**66.2.2 Unit Test Purpose.** Unit Tests shall verify that small pieces of Foundry work behave as specified before they are integrated into Builds, Packs, Rails, Dashboards, Connectors, Agents, Studio Runtime Packages, Marketplace Objects, Registry integrations, Deployment Units, National Portfolio objects, or handoff dependency packages. Unit Tests shall reduce local defects; they shall not validate system-level readiness.

**66.2.3 Unit Test Record.** Each material unit-test suite shall have a Unit Test Record identifying tested component, version, test cases, expected behavior, test data, environment, dependencies, coverage limitations, failures, fixes, reviewer where required, correction pathway, archive rule, and prohibited interpretations.

**66.2.4 Unit Test Scope.** Unit Tests may cover parsing, validation, formatting, calculation, API request construction, metadata generation, schema validation, public-safe label preservation, no-conversion statement inclusion, access-control logic, connector field mapping, dashboard label rendering, agent permission configuration, and teardown step execution.

**66.2.5 Unit Test Limits.** Unit Tests shall not be used to claim integration readiness, security assurance, public-safe communication safety, data permission, AI safety, dashboard interpretability, deployment readiness, or lawful handoff readiness unless supported by additional required reviews and tests.

**66.2.6 Unit Test Automation.** Unit Tests may be automated through repository workflows, CI pipelines, build scripts, local harnesses, or controlled Studio environments where appropriate. Automated unit tests shall not bypass review where human review is required.

**66.2.7 Unit Test Boundary.** Passing Unit Tests, test coverage, automated workflow success, or repository badge shall not create certification, public authority approval, procurement status, financeability, maturity status, consent, deployment authorization, operational readiness, or execution authority.

**66.2.8 Unit Test Correction.** Unit Test Records shall be corrected where tests are incomplete, brittle, misleading, stale, disconnected from specifications, dependent on unsafe data, or used to overclaim system quality.

**66.2.9 Unit Test Formula.** Unit Tests shall follow the formula: **test the smallest meaningful component; record expected behavior and limits; automate where useful; fix local defects early; never let unit-test success become system validation or deployment authority.**

***

### 66.3 Integration Tests

**66.3.1 Integration Test Identity.** **Integration Tests** shall be governed tests of how Foundry components work together across modules, services, schemas, connectors, agents, dashboards, data rooms, secure rooms, Studio runtimes, Marketplace surfaces, Registry surfaces, Observatory pipelines, Publication workflows, support workflows, correction workflows, teardown workflows, and handoff dependency packages.

**66.3.2 Integration Test Purpose.** Integration Tests shall verify that recomposed Foundry components preserve source records, metadata, security controls, data classifications, public-safe labels, support states, Registry states, Marketplace metadata, Studio labels, national routing fields, safeguard fields, and correction pathways when connected. Integration testing shall test composition, not merely component success.

**66.3.3 Integration Test Record.** Each Integration Test shall have an Integration Test Record identifying integrated components, versions, interfaces, environment, test data, expected interactions, dependency assumptions, access rules, data flows, AI involvement where applicable, security controls, failures, limitations, reviewer, correction pathway, archive rule, and prohibited interpretations.

**66.3.4 Integration Test Classes.** Integration Tests may include Pack integration tests, Rail workflow tests, connector-to-dashboard tests, schema-to-Registry tests, Marketplace-to-Registry link tests, Registry-to-Studio link tests, AI-agent-to-tool tests, data-room-to-output-review tests, secure-room-to-archive tests, Observatory-to-dashboard tests, National Portfolio-to-Registry tests, support-to-correction tests, and teardown-to-archive tests.

**66.3.5 Integration Failure Modes.** Integration Tests shall check for field loss, label loss, status mismatch, broken permissions, missing no-conversion language, overbroad data flow, tool overreach, connector failure, stale Registry state, misleading Marketplace display, Studio output mislabeling, support status mismatch, and archive confusion.

**66.3.6 Integration and Environment Limits.** Integration Tests shall state environment and scope. Integration success in Studio, test, synthetic-data, secure-room, Core Build, or demonstration environment shall not imply production deployment success, national legal suitability, procurement readiness, or operational authorization.

**66.3.7 Integration Test Boundary.** Passing Integration Tests, successful data flow, successful dashboard display, successful Registry link, successful Marketplace link, successful Studio interaction, or successful Core Build integration shall not create certification, public authority approval, procurement status, financeability, consent, maturity status, deployment authorization, operational command, or execution authority.

**66.3.8 Integration Test Correction.** Integration Test Records shall be corrected where integration assumptions change, field loss is discovered, permissions fail, labels are stripped, data flows exceed scope, Registry and Marketplace states diverge, or integration success is overclaimed.

**66.3.9 Integration Test Formula.** Integration Tests shall follow the formula: **test how components behave together; preserve fields, labels, permissions, and records; state environment limits; correct integration drift; never let integration success become deployment or approval.**

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### 66.4 Interoperability Tests

**66.4.1 Interoperability Test Identity.** **Interoperability Tests** shall be governed tests of whether Foundry objects exchange information, records, metadata, schemas, labels, states, outputs, API responses, connector payloads, dashboard states, Marketplace metadata, Registry states, Studio runtime metadata, Observatory signals, readiness mappings, safeguard records, support records, correction records, and archive references with other systems while preserving meaning, security, and control.

**66.4.2 Interoperability Test Purpose.** Interoperability Tests shall verify technical and semantic exchange across providers, platforms, clouds, national systems, repositories, data rooms, secure rooms, Studio environments, Marketplace surfaces, Registry surfaces, Observatory systems, dashboards, and handoff-adjacent recipients. Interoperability shall be tested to avoid lock-in and semantic drift; it shall not create provider validation.

**66.4.3 Interoperability Test Record.** Each Interoperability Test shall have an Interoperability Test Record identifying systems tested, versions, interface specifications, schemas, authentication method, authorization method, data classes, metadata classes, semantic fields, test data, expected exchange, actual exchange, failures, limitations, provider dependencies, reviewer, correction pathway, archive rule, and prohibited interpretations.

**66.4.4 Semantic Preservation.** Interoperability Tests shall verify preservation of source identifiers, version identifiers, confidence labels, uncertainty labels, drift labels, public-safe labels, support states, Registry states, Marketplace states, Studio states, national routing fields, safeguard fields, no-conversion statements, correction links, and archive links.

**66.4.5 Provider-Neutrality Testing.** Interoperability Tests shall identify provider-specific assumptions, proprietary interface dependencies, managed-service dependencies, data export limits, API rate limits, vendor-specific metadata, portability constraints, and substitution barriers.

**66.4.6 Failure and Negative Tests.** Interoperability Tests shall include negative cases where authorization fails, schema mismatch occurs, prohibited data transfer is attempted, labels are missing, unsupported versions are used, endpoints are unavailable, or data residency prevents transfer.

**66.4.7 Interoperability Test Boundary.** Successful interoperability, API compatibility, connector compatibility, cross-platform exchange, multi-cloud exchange, or national exchange shall not create certification, provider validation, procurement status, financeability, public authority approval, consent, deployment authorization, operational command, or execution authority.

**66.4.8 Interoperability Test Correction.** Interoperability Test Records shall be corrected where semantic fields are lost, provider assumptions are hidden, public-safe labels are stripped, national routing is bypassed, secure-room restrictions fail, or interoperability results are used as approval or preferred-vendor evidence.

**66.4.9 Interoperability Test Formula.** Interoperability Tests shall follow the formula: **test exchange and meaning; preserve labels and states; test failure modes; disclose provider limits; correct semantic drift; never let interoperability become certification, provider preference, procurement, finance, consent, deployment, or execution.**

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### 66.5 Security Tests

**66.5.1 Security Test Identity.** **Security Tests** shall be governed, authorized, scope-bound tests of Foundry security controls, including identity, access, privileged access, secrets, keys, certificates, secure configuration, dependency vulnerabilities, APIs, connectors, agents, dashboards, data rooms, secure rooms, Studio runtimes, Marketplace surfaces, Registry surfaces, cloud resources, network routes, storage, edge environments, Observatory systems, infrastructure templates, Golden Images, logging where appropriate, monitoring where appropriate, egress controls, and teardown closure.

**66.5.2 Security Test Purpose.** Security Tests shall identify weaknesses, verify controls, support remediation, and reduce risk within recorded scope. Security Tests shall not certify cybersecurity, guarantee security, authorize deployment, or replace legal compliance review.

**66.5.3 Security Test Record.** Each Security Test shall have a Security Test Record identifying object, environment, test scope, authorized testers, permitted methods, prohibited methods, data class, access class, tools used, findings, severity, remediation, residual risk, disclosure limits, reviewer, correction pathway, archive rule, and prohibited interpretations.

**66.5.4 Security Test Classes.** Security Tests may include vulnerability scans, dependency scans, secrets scans, configuration tests, access-control tests, privileged-access tests, API security tests, connector security tests, agent tool-permission tests, dashboard exposure tests, data-room output-control tests, secure-room egress tests, cloud security tests, network segmentation tests, and teardown access-closure tests.

**66.5.5 Authorized Scope.** Security Tests shall be performed only within lawful, recorded authorization. Foundry Security Tests shall not authorize uncontrolled penetration testing, exploit deployment, credential probing, data exfiltration, live-system attack, third-party system testing, or public vulnerability disclosure outside approved scope.

**66.5.6 Sensitive Findings Control.** Security findings shall be access-controlled where disclosure could create risk. Public-safe summaries may describe categories, remediation, and learning without exposing exploitable details.

**66.5.7 Security Test Boundary.** Passing Security Tests, low vulnerability count, remediation closure, secure-room test success, or security dashboard status shall not create cybersecurity certification, legal compliance certification, public authority approval, procurement status, financeability, insurability, consent, deployment authorization, operational readiness, or execution authority.

**66.5.8 Security Test Correction.** Security Test Records shall be corrected where scope is misstated, findings are hidden, severity is understated, remediation is overstated, new vulnerabilities appear, secrets are exposed, or security testing is treated as certification.

**66.5.9 Security Test Formula.** Security Tests shall follow the formula: **test security only within authorization; protect findings; remediate and record residual risk; restrict unsafe objects; correct security drift; never let test success become cybersecurity certification or deployment approval.**

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### 66.6 Performance Tests

**66.6.1 Performance Test Identity.** **Performance Tests** shall be governed tests of speed, throughput, latency, capacity, scalability within scope, resource utilization, availability within support class, dashboard responsiveness, connector throughput, API performance, AI inference performance, data-room performance, secure-room performance, Studio runtime performance, Observatory pipeline performance, network performance, compute performance, storage performance, and degraded-mode behavior.

**66.6.2 Performance Test Purpose.** Performance Tests shall help Foundry understand whether systems perform adequately for recorded use cases, environments, audiences, and support classes. Performance Tests shall not become generalized benchmarks, provider rankings, procurement evidence, financeability signals, maturity ratings, or deployment authorizations.

**66.6.3 Performance Test Record.** Each Performance Test shall have a Performance Test Record identifying object, version, workload, environment, data class, provider or host where relevant, hardware, software, network, configuration, test duration, metrics, baseline, expected result, actual result, limitations, reproducibility status, reviewer, correction pathway, archive rule, and prohibited interpretations.

**66.6.4 Performance Metric Classes.** Performance metrics may include response time, latency, throughput, job completion time, concurrency, error rate, resource utilization, cost or resource burden where relevant, energy or resilience considerations where relevant, degraded-mode performance, recovery time, and support-class availability.

**66.6.5 Environment Limitation.** Performance results shall be labeled by environment. Core Build performance shall not be generalized to field deployment. Studio performance shall not be generalized to operational use. Cloud performance shall not be generalized to sovereign compute. Synthetic data performance shall not be generalized to restricted data.

**66.6.6 Comparative Performance Controls.** Comparative performance tests involving providers, clouds, models, hardware, networks, or proprietary components shall follow Benchmark Neutrality. Comparative outputs shall not imply preferred vendor status or procurement recommendation.

**66.6.7 Performance Test Boundary.** Performance Test completion, performance result, benchmark, dashboard, high throughput, low latency, Core Build performance, or Studio performance shall not create certification, provider validation, procurement status, financeability, public authority approval, maturity status, consent, deployment authorization, operational readiness, or execution authority.

**66.6.8 Performance Test Correction.** Performance Test Records shall be corrected where environment is misstated, workload is unrepresentative, results are stale, provider versions change, limitations are hidden, or performance results are used as provider ranking or deployment approval.

**66.6.9 Performance Test Formula.** Performance Tests shall follow the formula: **measure performance in a defined environment with a defined workload; state limits and reproducibility; control comparisons; correct stale results; never let performance become certification, procurement signal, finance signal, or deployment authority.**

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### 66.7 Simulation Tests

**66.7.1 Simulation Test Identity.** **Simulation Tests** shall be governed tests using models, scenarios, synthetic environments, digital twins, tabletop exercises, system dynamics, agent-based models, stress tests, degraded-mode exercises, disaster-risk scenarios, public authority learning scenarios, Studio scenarios, Core Build scenarios, Observatory scenarios, readiness scenarios, safeguard scenarios, and handoff dependency scenarios to examine behavior under defined assumptions.

**66.7.2 Simulation Test Purpose.** Simulation Tests shall support learning, foresight, scenario discipline, evidence formation, public authority learning, National Portfolio preparation, readiness mapping, safeguard review, Studio runtime testing, Observatory pipeline testing, and Core Build preparation. Simulation Tests shall not predict the future, approve deployment, create public warnings, or determine public authority action.

**66.7.3 Simulation Test Record.** Each Simulation Test shall have a Simulation Test Record identifying simulation purpose, model or scenario, assumptions, parameters, data inputs, synthetic data, environment, actors represented, limitations, uncertainty, sensitivity analysis where applicable, AI involvement where applicable, outputs, interpretation limits, reviewer, correction pathway, archive rule, and prohibited interpretations.

**66.7.4 Simulation Classes.** Simulation Tests may include technical simulation, infrastructure simulation, cyber range simulation, AI behavior simulation, digital twin simulation, disaster scenario simulation, climate or nature scenario simulation, supply chain scenario simulation, public authority learning simulation, finance-readiness scenario simulation, National Portfolio simulation, and handoff dependency simulation.

**66.7.5 Simulation Assumption Discipline.** Simulation outputs shall state assumptions, excluded variables, uncertainty, model limits, data limits, environmental limits, and non-transferability. Simulation outputs shall not be presented as forecasts, official classifications, warnings, or deployment decisions.

**66.7.6 Public-Safe Simulation Outputs.** Public-safe simulation materials shall avoid panic, official warning implication, false precision, unsupported ranking, public authority overclaim, finance or procurement overclaim, and operational command language.

**66.7.7 Simulation Test Boundary.** Simulation completion, scenario result, digital twin output, stress-test result, Studio scenario, public authority learning scenario, or Core Build simulation shall not create public warning, official classification, certification, procurement status, financeability, public authority approval, consent, deployment authorization, operational command, or execution authority.

**66.7.8 Simulation Test Correction.** Simulation Test Records shall be corrected where assumptions are wrong, outputs are overinterpreted, models drift, public-safe language fails, public authority users treat outputs as decisions, or simulations are used as deployment evidence.

**66.7.9 Simulation Test Formula.** Simulation Tests shall follow the formula: **model scenarios with explicit assumptions; label uncertainty and limits; use outputs for learning and review; correct overinterpretation; never let simulation become prediction, public warning, approval, deployment, or execution.**

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### 66.8 Data Quality Tests

**66.8.1 Data Quality Test Identity.** **Data Quality Tests** shall be governed tests of data completeness, consistency, validity, provenance, metadata sufficiency, timeliness, duplication, missingness, schema conformance, range checks, outlier handling, lineage, transformation integrity, residency status, classification integrity, output-review status, and suitability for recorded Foundry purposes.

**66.8.2 Data Quality Test Purpose.** Data Quality Tests shall help Foundry understand whether data can support Evidence Products, Dashboards, Observatory pipelines, DRI outputs, AI workflows, Studio runtimes, National Portfolio materials, public-safe summaries, readiness mappings, and handoff dependency packages within recorded limits. Data quality shall not create data permission or universal truth.

**66.8.3 Data Quality Test Record.** Each Data Quality Test shall have a Data Quality Test Record identifying dataset, version, source, steward, data class, test purpose, test rules, metadata reviewed, provenance reviewed, results, missingness, outliers, transformations, limitations, permitted uses, prohibited uses, reviewer, correction pathway, archive rule, and prohibited interpretations.

**66.8.4 Data Quality Test Classes.** Data Quality Tests may include schema conformance tests, metadata completeness tests, provenance tests, duplication tests, missingness tests, range tests, temporal consistency tests, geospatial consistency tests, transformation tests, aggregation tests, anonymization or masking tests, public-safe output tests, and AI-readiness data tests where permitted.

**66.8.5 Sensitive Data Controls.** Data Quality Tests shall not expose restricted data, protected knowledge, Indigenous-sensitive knowledge where applicable, public authority-sensitive data, health-sensitive data, infrastructure-sensitive data, cyber-sensitive data, or national-sensitive data beyond approved environment and output-review controls.

**66.8.6 AI Readiness Distinction.** Data Quality Tests may inform whether data is technically suitable for an AI workflow, but shall not authorize AI use unless AI-use permission and AI Review are separately recorded.

**66.8.7 Data Quality Test Boundary.** Data quality score, test pass, metadata completeness, provenance record, or public-safe aggregate shall not create data ownership, unrestricted use rights, publication permission, AI training permission, public authority approval, procurement status, financeability, consent, deployment authorization, or execution authority.

**66.8.8 Data Quality Test Correction.** Data Quality Test Records shall be corrected where tests are incomplete, data changes, metadata is wrong, transformations fail, sensitivity is missed, AI readiness is overclaimed, or data quality is treated as permission.

**66.8.9 Data Quality Test Formula.** Data Quality Tests shall follow the formula: **test data against recorded purpose; preserve provenance and classification; protect sensitive outputs; correct quality drift; never let data quality become data permission, universal truth, consent, deployment, or execution.**

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### 66.9 AI Output Tests

**66.9.1 AI Output Test Identity.** **AI Output Tests** shall be governed tests of outputs generated by AI models, AI systems, agents, retrieval workflows, summarization workflows, translation workflows, classification workflows, dashboard agents, Studio agents, publication-assist agents, evidence-assist agents, readiness-assist agents, and support agents used by Foundry.

**66.9.2 AI Output Test Purpose.** AI Output Tests shall assess whether AI outputs remain within source records, avoid unsupported claims, preserve public-safe language, respect data restrictions, avoid hallucinated authority, follow no-conversion rules, avoid finance or procurement overclaim, avoid public authority overclaim, avoid consent inference, respect safeguard boundaries, and remain subject to human review.

**66.9.3 AI Output Test Record.** Each AI Output Test shall have an AI Output Test Record identifying model, system, agent, workflow, prompt or workflow class where appropriate, data inputs, retrieval sources, tool permissions, output type, test cases, expected behavior, actual outputs, failure modes, human-review findings, red-team findings where applicable, correction pathway, archive rule, and prohibited interpretations.

**66.9.4 AI Output Test Classes.** AI Output Tests may include hallucination tests, citation/source-grounding tests, no-conversion language tests, public authority overclaim tests, finance overclaim tests, procurement overclaim tests, consent overclaim tests, protected knowledge exposure tests, sensitive data leakage tests, prompt-injection tests, tool-misuse tests, translation fidelity tests, summary fidelity tests, and automated claim-prevention tests.

**66.9.5 Human Review Requirement.** AI Output Tests shall not be solely self-graded by the AI system being tested where authority-sensitive, public-safe, data-sensitive, finance-sensitive, procurement-sensitive, public authority-sensitive, safeguard-sensitive, or release-relevant outputs are involved. Human review shall be recorded.

**66.9.6 AI Output Labels.** Tested AI outputs shall be labeled according to status, including draft, review-support, analysis-support, restricted, public-safe candidate, reviewed, rejected, corrected, archived, or prohibited. Test outputs shall not be used as release outputs unless separately reviewed.

**66.9.7 AI Output Test Boundary.** AI Output Test completion, passing evaluation, red-team result, automated claim-prevention result, or human-reviewed sample shall not certify AI safety, authorize sensitive data use, create public authority approval, procurement status, financeability, consent, deployment authorization, operational command, or execution authority.

**66.9.8 AI Output Test Correction.** AI Output Test Records shall be corrected where model versions change, retrieval sources change, prompts change, tools change, outputs overclaim, leakage occurs, red-team findings are missed, or AI output test success is treated as AI certification.

**66.9.9 AI Output Test Formula.** AI Output Tests shall follow the formula: **test outputs against sources, claims limits, data limits, and human review; record failures; restrict outputs by status; correct AI drift; never let AI output testing become AI certification, approval, consent, deployment, or execution.**

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### 66.10 Dashboard Tests

**66.10.1 Dashboard Test Identity.** **Dashboard Tests** shall be governed tests of dashboard data sources, indicator logic, maps, charts, labels, confidence indicators, uncertainty indicators, drift indicators, access controls, export controls, refresh behavior, public-safe language, accessibility, translation, user interpretation, Registry links, Marketplace links, Studio links, National Portfolio views, Observatory views, DRI views, readiness views, and archive views.

**66.10.2 Dashboard Test Purpose.** Dashboard Tests shall ensure that dashboards display bounded information accurately, accessibly, securely, and public-safely within their intended audience and use. Dashboard Tests shall prevent visual systems from implying warning, rating, official classification, procurement signal, finance signal, consent, deployment authorization, or operational command.

**66.10.3 Dashboard Test Record.** Each Dashboard Test shall have a Dashboard Test Record identifying dashboard, version, audience, source records, data sources, indicators, visualization components, labels tested, access controls tested, export controls tested, public-safe language tested, accessibility tested, refresh tested, failure modes, reviewer, correction pathway, archive rule, and prohibited interpretations.

**66.10.4 Dashboard Test Classes.** Dashboard Tests may include data-refresh tests, label-visibility tests, confidence-label tests, uncertainty-label tests, drift-label tests, access-control tests, export-control tests, map-sensitivity tests, threshold-interpretation tests, color-meaning tests, tooltip tests, accessibility tests, translation tests, screenshot tests, embedded-view tests, and archive-snapshot tests.

**66.10.5 Visual Meaning Tests.** Dashboard Tests shall examine whether visual design creates false precision, alarm, ranking, rating, provider preference, national ranking, public authority implication, procurement implication, finance implication, consent implication, deployment implication, or command implication.

**66.10.6 Dashboard User Testing.** Where appropriate, Dashboard Tests may include user interpretation testing with intended audiences. User confusion shall trigger public-safe correction, label correction, access restriction, or withdrawal.

**66.10.7 Dashboard Test Boundary.** Dashboard test pass, dashboard activation, label review, public-safe display, dashboard user testing, or dashboard refresh success shall not create public warning, official classification, public authority approval, procurement status, financeability, consent, deployment authorization, operational command, or execution authority.

**66.10.8 Dashboard Test Correction.** Dashboard Test Records shall be corrected where labels fail, data is stale, access controls fail, exports expose restricted content, visuals mislead, users misunderstand, or dashboard testing is treated as decision authority.

**66.10.9 Dashboard Test Formula.** Dashboard Tests shall follow the formula: **test data, labels, access, exports, accessibility, and public meaning; correct misleading visuals; withdraw unsafe displays; never let dashboard testing become warning, rating, approval, deployment, or execution.**

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### 66.11 Connector Tests

**66.11.1 Connector Test Identity.** **Connector Tests** shall be governed tests of Connectors, APIs, integrations, webhooks, data links, Registry links, Marketplace links, Studio links, Observatory links, National Node exchanges, secure-room pathways, compute-to-data pathways, handoff interfaces, authentication, authorization, schema mapping, metadata preservation, label preservation, egress controls, error handling, logging where appropriate, support behavior, and teardown.

**66.11.2 Connector Test Purpose.** Connector Tests shall ensure that interfaces move only what they are permitted to move, preserve meaning, respect access controls, fail safely, support correction, and can be disconnected. Connector Tests shall preserve that connection is not permission.

**66.11.3 Connector Test Record.** Each Connector Test shall have a Connector Test Record identifying connector, version, source system, destination system, data classes, metadata classes, permitted operations, prohibited operations, authentication method, authorization method, test cases, expected data flows, actual data flows, failure modes, security findings, reviewer, correction pathway, archive rule, and prohibited interpretations.

**66.11.4 Connector Test Classes.** Connector Tests may include authentication tests, authorization tests, schema mapping tests, metadata preservation tests, public-safe label preservation tests, Registry state preservation tests, Marketplace metadata preservation tests, Studio metadata preservation tests, data-residency tests, egress tests, prohibited-transfer tests, rate-limit tests, error-handling tests, retry tests, logging tests where appropriate, and teardown tests.

**66.11.5 Negative Connector Tests.** Connector Tests shall include negative tests for unauthorized access, expired credentials, prohibited data transfer, schema mismatch, missing labels, unsupported versions, network failure, restricted national data, secure-room-only data, and output-review bypass.

**66.11.6 Connector Teardown Testing.** Connector Tests shall verify that credentials, tokens, keys, certificates, webhooks, routes, firewall rules, service accounts, and data flows can be revoked, closed, or suspended.

**66.11.7 Connector Test Boundary.** Connector test success, successful sync, API response, interoperability result, National Node exchange, secure-room connector success, or compute-to-data connector success shall not create data permission, public authority approval, procurement status, financeability, consent, deployment authorization, operational command, or execution authority.

**66.11.8 Connector Test Correction.** Connector Test Records shall be corrected where data flows exceed scope, authorization fails, egress controls fail, schema mappings lose meaning, labels are stripped, national routing is bypassed, or connector testing is treated as permission.

**66.11.9 Connector Test Formula.** Connector Tests shall follow the formula: **test permitted and prohibited flows; preserve schemas and labels; fail closed; verify revocation; correct connector drift; never let connector success become permission or authority.**

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### 66.12 Secure Room Tests

**66.12.1 Secure Room Test Identity.** **Secure Room Tests** shall be governed tests of secure rooms, clean rooms, no-download rooms, confidential computing rooms, restricted AI rooms, cyber-sensitive rooms, public authority-sensitive rooms, protected knowledge rooms, Indigenous-sensitive rooms where applicable, incident rooms, legal-sensitive rooms, and other restricted Foundry environments.

**66.12.2 Secure Room Test Purpose.** Secure Room Tests shall verify that restricted environments enforce identity controls, access controls, privileged access controls, device controls where applicable, network controls, storage controls, compute controls, tool controls, AI-use rules, no-download rules, no-export rules, egress controls, output-review rules, logging rules where appropriate, monitoring rules where appropriate, incident pathways, support controls, closure controls, and archive controls.

**66.12.3 Secure Room Test Record.** Each Secure Room Test shall have a Secure Room Test Record identifying secure room, purpose, environment class, data and material classes, user classes, controls tested, tools tested, AI rules tested, output review tested, egress tested, incident pathway tested, closure tested, findings, remediation, residual risk, reviewer, correction pathway, archive rule, and prohibited interpretations.

**66.12.4 Secure Room Test Classes.** Secure Room Tests may include identity tests, access tests, privileged access tests, no-download tests, no-export tests, egress tests, output-review tests, approved-tool tests, prohibited-tool tests, AI-use tests, logging tests where appropriate, monitoring tests where appropriate, screenshot-control tests where appropriate, connector-closure tests, credential-revocation tests, and archive tests.

**66.12.5 Output and Egress Testing.** Secure Room Tests shall verify that outputs cannot leave without required review, that prohibited exports are blocked, that public-safe summaries preserve restrictions, and that restricted content is not exposed through logs, screenshots, embeddings, temporary files, caches, or derived outputs.

**66.12.6 Incident Pathway Testing.** Secure Room Tests shall verify that unauthorized access, output-review bypass, data leakage, AI leakage, protected knowledge exposure, Indigenous protocol concern where applicable, and cyber-sensitive exposure trigger containment and correction pathways.

**66.12.7 Secure Room Test Boundary.** Secure Room test completion, control pass, output-review pass, or secure-room readiness shall not create legal compliance certification, cybersecurity certification, public authority approval, procurement status, financeability, consent, deployment authorization, operational command, or execution authority.

**66.12.8 Secure Room Test Correction.** Secure Room Test Records shall be corrected where controls fail, outputs leak, AI exceeds scope, access is overbroad, no-download fails, protected knowledge is exposed, or secure-room testing is treated as certification.

**66.12.9 Secure Room Test Formula.** Secure Room Tests shall follow the formula: **test restricted environment controls; block raw egress; verify output review and incident pathways; close access when needed; never let secure-room test success become certification, consent, or execution.**

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### 66.13 Public-Safe Publication Tests

**66.13.1 Public-Safe Publication Test Identity.** **Public-Safe Publication Tests** shall be governed tests applied to public-facing, controlled-public, public authority learning, Marketplace-facing, Registry-facing, Studio-facing, Academy-facing, National Portfolio-facing, Nexus Universe-facing, Core Build-facing, media-facing, correction, withdrawal, and archive materials before or after release to ensure that public meaning remains safe, bounded, accessible, source-grounded, and correctionable.

**66.13.2 Public-Safe Publication Test Purpose.** Public-Safe Publication Tests shall detect unsupported claims, public warning implications, official classification implications, public authority overclaims, finance or procurement overclaims, maturity overclaims, provider endorsements, sponsor-control implications, consent implications, deployment implications, operational command language, accessibility failures, translation drift, and visual overclaim before harm occurs.

**66.13.3 Public-Safe Publication Test Record.** Each Publication Test shall have a Public-Safe Publication Test Record identifying material, audience, channel, source records, labels tested, boundary language tested, accessibility tested, translation tested where applicable, visual elements tested, public authority sensitivity, finance sensitivity, procurement sensitivity, safeguard sensitivity, findings, required revisions, reviewer, correction pathway, archive rule, and prohibited interpretations.

**66.13.4 Publication Test Classes.** Publication Tests may include claims tests, no-conversion statement tests, public authority boundary tests, finance boundary tests, procurement neutrality tests, consent-boundary tests, provider-neutrality tests, sponsor-neutrality tests, visual meaning tests, accessibility tests, translation tests, metadata tests, link tests, correction-link tests, withdrawal-notice tests, and archive-label tests.

**66.13.5 Readability and Accessibility Testing.** Public-safe publication testing shall examine whether intended audiences can understand the material, including limitations, support status, correction pathways, and no-conversion boundaries. Plain-language summaries shall not remove essential boundary language.

**66.13.6 Channel-Specific Testing.** Materials shall be tested against their actual channel. Slide decks, dashboards, social materials, reports, Marketplace descriptions, Registry records, Studio instructions, public authority briefs, capital-reader materials, media statements, and community-facing materials shall not be assumed safe because another version was reviewed.

**66.13.7 Public-Safe Publication Test Boundary.** Passing Public-Safe Publication Tests, release approval, accessible format, translated version, public-safe label, or public release shall not create public warning, official classification, public authority approval, certification, procurement status, financeability, consent, deployment authorization, or execution authority.

**66.13.8 Public-Safe Publication Test Correction.** Test Records shall be corrected where wording misleads, labels are missing, translations alter boundaries, accessibility fails, visual design overclaims, public authority meaning is overstated, or publication testing is treated as official status.

**66.13.9 Public-Safe Publication Test Formula.** Public-Safe Publication Tests shall follow the formula: **test public meaning by audience and channel; preserve labels and boundaries; correct unsafe communication; withdraw when required; never let publication testing become official warning, approval, certification, consent, deployment, or execution.**

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### 66.14 Marketplace Listing Tests

**66.14.1 Marketplace Listing Test Identity.** **Marketplace Listing Tests** shall be governed tests of Marketplace listings, categories, metadata, search fields, filters, support-status displays, dependency disclosures, license terms, provider disclosures, sponsor disclosures, Registry references, Studio references, national localization fields, public-safe descriptions, correction links, delisting functions, and archive labels.

**66.14.2 Marketplace Listing Test Purpose.** Marketplace Listing Tests shall ensure discovery without endorsement. They shall detect whether listing design, metadata, search behavior, ranking, featured placement, categories, descriptions, downloads, support labels, or Registry / Studio links imply approval, certification, preferred-vendor status, procurement readiness, financeability, public authority approval, deployment readiness, or execution authority.

**66.14.3 Marketplace Listing Test Record.** Each Marketplace Listing Test shall have a record identifying listing, object class, metadata fields, support status, Registry link, Studio link, provider or sponsor relationship where applicable, public-safe description, search behavior, category placement, ranking or display behavior, correction link, delisting pathway, findings, reviewer, correction pathway, archive rule, and prohibited interpretations.

**66.14.4 Listing Metadata Tests.** Listing tests shall verify title, description, version, support class, license, dependencies, provider dependencies, sponsor involvement, public-safe limits, data requirements, AI requirements, security notes, national localization, Registry link, Studio link, correction link, and archive status.

**66.14.5 Search and Ranking Tests.** Marketplace Listing Tests shall examine whether search, filters, featured placement, recommendation logic, popularity displays, download counts, or categories create provider preference, procurement implication, endorsement implication, or false maturity.

**66.14.6 Delisting and Correction Tests.** Marketplace Listing Tests shall verify that listings can be corrected, restricted, suspended, delisted, withdrawn, archived, or reinstated by record and that such changes propagate to related Registry and Studio references where applicable.

**66.14.7 Marketplace Listing Test Boundary.** Passing Marketplace Listing Tests, listing publication, search visibility, featured placement, download availability, Registry link, or Studio link shall not create recognition, certification, procurement preference, financeability, insurability, provider validation, public authority approval, consent, deployment authorization, or execution authority.

**66.14.8 Marketplace Listing Test Correction.** Test Records shall be corrected where metadata is stale, support status is wrong, search ranking implies preference, provider or sponsor influence is hidden, Registry links mislead, Studio links mislead, or Marketplace listing is treated as endorsement.

**66.14.9 Marketplace Listing Test Formula.** Marketplace Listing Tests shall follow the formula: **test discovery metadata and display behavior; show support, dependencies, and limits; verify correction and delisting; never let Marketplace testing or listing become endorsement, procurement, finance, consent, deployment, or execution.**

***

### 66.15 Studio Runtime Tests

**66.15.1 Studio Runtime Test Identity.** **Studio Runtime Tests** shall be governed tests of Nexus Studio runtime packages, user sessions, access controls, data restrictions, tool permissions, agent permissions, output labels, output-review rules, session limits, export rules, dashboard interpretation, simulation behavior, Marketplace previews, Registry references, support behavior, shutdown triggers, correction pathways, retirement, and archive.

**66.15.2 Studio Runtime Test Purpose.** Studio Runtime Tests shall verify that controlled interaction remains controlled. They shall ensure that users can learn, simulate, explore, demonstrate, prepare, or review within the Studio without converting runtime interaction into public authority decision, procurement signal, finance signal, consent, deployment authorization, operational command, or execution.

**66.15.3 Studio Runtime Test Record.** Each Studio Runtime Test shall have a Studio Runtime Test Record identifying runtime package, version, user class, access class, data class, tool class, agent class, session class, test cases, output classes, output-review requirements, support status, Registry relationship, Marketplace relationship, national routing relationship, findings, reviewer, correction pathway, archive rule, and prohibited interpretations.

**66.15.4 Studio Test Classes.** Studio Runtime Tests may include access-control tests, session-limit tests, data-restriction tests, no-download tests, export-control tests, tool-permission tests, agent-boundary tests, AI output-label tests, dashboard-interpretation tests, simulation-output tests, public-safe language tests, output-review tests, support tests, shutdown-trigger tests, Marketplace-preview tests, Registry-reference tests, and archive tests.

**66.15.5 User Misinterpretation Tests.** Studio Runtime Tests shall examine whether intended users understand that Studio outputs are learning, simulation, demonstration, review-support, readiness-support, or exploration outputs, not official decisions, procurement recommendations, finance conclusions, consent records, deployment authorizations, or operational commands.

**66.15.6 Shutdown and Pause Tests.** Studio Runtime Tests shall verify that runtimes can be paused, restricted, shut down, corrected, withdrawn, retired, or archived where data risk, AI overreach, tool misuse, public-safe risk, support lapse, or user misunderstanding appears.

**66.15.7 Studio Runtime Test Boundary.** Passing Studio Runtime Tests, Studio-ready status, Studio-active status, session success, dashboard interaction, simulation result, agent output, public authority participation, capital-reader viewing, Marketplace preview, or Registry reference shall not create public authority decision, procurement status, financeability, insurability, consent, deployment authorization, operational command, or execution authority.

**66.15.8 Studio Runtime Test Correction.** Studio Runtime Test Records shall be corrected where access controls fail, tools exceed scope, agents overreach, outputs are mislabeled, exports are unsafe, users misunderstand runtime status, or Studio testing is treated as deployment approval.

**66.15.9 Studio Runtime Test Formula.** Studio Runtime Tests shall follow the formula: **test controlled runtime, users, data, tools, agents, labels, and shutdown; correct misuse; archive non-current runtime; never let Studio test success become approval, consent, deployment, or execution.**

***

### 66.16 Teardown Tests

**66.16.1 Teardown Test Identity.** **Teardown Tests** shall be governed tests of whether Foundry resources, environments, objects, access rights, credentials, keys, certificates, routes, APIs, connectors, webhooks, cloud resources, storage, data rooms, secure rooms, dashboards, Studio runtimes, AI agents, Marketplace listings, Registry states, support records, public links, publication channels, logs where appropriate, and archive packages can be closed, revoked, deleted, sealed, delisted, withdrawn, retired, archived, or verified as non-current.

**66.16.2 Teardown Test Purpose.** Teardown Tests shall prevent temporary systems, Core Build environments, Nexus Universe demonstrations, Studio sessions, public dashboards, connectors, AI agents, cloud resources, data rooms, secure rooms, public links, and support assumptions from persisting by drift. They shall ensure that closure is engineered, not improvised.

**66.16.3 Teardown Test Record.** Each Teardown Test shall have a Teardown Test Record identifying object, environment, teardown trigger, resources tested, access revocation, credential rotation, key and certificate revocation, connector closure, API shutdown, network route removal, storage disposition, data deletion or sealing, dashboard withdrawal, Studio shutdown, Marketplace delisting, Registry update, support closure, public-safe notice, archive package, verification results, reviewer, correction pathway, and prohibited interpretations.

**66.16.4 Teardown Test Classes.** Teardown Tests may include access-closure tests, credential-revocation tests, certificate-revocation tests, DNS removal tests, firewall-rule removal tests, connector shutdown tests, API deactivation tests, cloud deletion tests, storage deletion tests, data-room closure tests, secure-room closure tests, agent shutdown tests, dashboard withdrawal tests, Studio pause tests, Marketplace delisting tests, Registry status update tests, support closure tests, public notice tests, and archive verification tests.

**66.16.5 Teardown Before Activation.** High-risk environments and temporary environments shall have teardown tests before activation where failure to close would create security, data, public-safe, provider-neutrality, support, national routing, or authority-overclaim risk.

**66.16.6 Teardown Verification.** Teardown Test outcomes shall identify what was closed, what remains, what is archived, what is sealed, what is deletion-verified, what requires ongoing retention, what is transferred to support, and what requires further correction.

**66.16.7 Teardown Test Boundary.** Teardown test completion, deletion verification, archive status, delisting, withdrawal, support closure, or non-continuation status shall not create legal finding, public authority finding, procurement finding, finance conclusion, consent determination, deployment denial, or execution effect beyond the Teardown Record.

**66.16.8 Teardown Test Correction.** Teardown Test Records shall be corrected where resources persist, credentials remain active, storage remains, public links remain, dashboards remain visible, Studio runtimes remain active, Marketplace listings remain, Registry states are stale, support closure is incomplete, or teardown is treated as external rejection.

**66.16.9 Teardown Test Formula.** Teardown Tests shall follow the formula: **test closure before reliance; revoke access and routes; dispose, seal, or archive data by rule; update Marketplace, Registry, Studio, and support records; verify closure; never let temporary infrastructure persist by drift.**

***

### 66.17 Test Records and Archive

**66.17.1 Test Record Principle.** **Test Records and Archive** shall preserve the identity, purpose, scope, environment, data, method, results, limitations, failures, corrections, reviewer, release relationship, support relationship, public-safe relationship, Registry relationship, Marketplace relationship, Studio relationship, National Portfolio relationship, handoff relationship, and archive status of Foundry tests. Testing shall have institutional memory.

**66.17.2 Test Record Elements.** Each material Test Record shall include test identifier, object tested, version, test class, source records, test purpose, environment, data class, test data description, method, tools, dependencies, expected results, actual results, failures, limitations, reviewer, conflicts where applicable, correction actions, retest requirement, release implication within scope, support implication within scope, archive rule, and prohibited interpretations.

**66.17.3 Test Result Classes.** Test result classes may include passed-within-scope, failed, inconclusive, partially passed, passed-with-limitations, blocked, not-applicable-by-record, restricted, superseded, withdrawn, corrected, retest-required, archive-only, or non-current. Result classes shall be defined by record and shall not imply external authority.

**66.17.4 Failure Preservation.** Failed, inconclusive, blocked, and partially passed tests shall be preserved where material. Foundry shall not delete or hide failed tests to preserve apparent quality. Failure records shall support correction, learning, support classification, release decisions, sunsetting, and archive.

**66.17.5 Test Archive Classes.** Test Archives may be public, controlled, restricted, secure, national, institutional-memory, correction, support, Marketplace, Registry, Studio, Core Build, Nexus Universe, National Portfolio, risk, sealed, deletion-verified, or non-continuation, depending on sensitivity and use.

**66.17.6 Test Reuse and Reinstatement.** Archived tests may be reused only after review confirming current relevance, source validity, dependency status, environment compatibility, data permission, AI behavior, security status, public-safe status, safeguard conditions, national routing, support status, and intended audience. Reusing an old test script shall not reinstate old assurance.

**66.17.7 Test Record Boundary.** Test Records, passing results, failure records, retest completion, archive records, dashboards, scorecards, badges, or test reports shall not create certification, accreditation, audit opinion, public authority approval, procurement status, financeability, insurability, maturity certification, consent, deployment authorization, operational readiness, or execution authority.

**66.17.8 Test Record Correction.** Test Records shall be corrected where scope is wrong, environment is misstated, data is unsafe, results are stale, failures are hidden, limitations are omitted, archive class is wrong, or test records are used as certification or deployment approval.

**66.17.9 Final Testing Architecture Formula.** The controlling Testing Architecture Formula is that **Test Harnesses create bounded test environments; Unit Tests verify discrete components without system validation; Integration Tests examine recomposed behavior without deployment approval; Interoperability Tests verify exchange and semantic preservation without provider validation; Security Tests reduce cyber risk within authorized scope without cybersecurity certification; Performance Tests measure defined workloads without vendor ranking or readiness overclaim; Simulation Tests support learning without prediction or official warning; Data Quality Tests assess data within purpose without permission; AI Output Tests check AI claims and boundaries without AI certification; Dashboard Tests test visualization without warning or decision authority; Connector Tests test permitted and prohibited flows without permission; Secure Room Tests test restricted controls without compliance certification; Public-Safe Publication Tests test public meaning without official status; Marketplace Listing Tests test discovery without endorsement; Studio Runtime Tests test controlled interaction without deployment; Teardown Tests test closure without external rejection; and Test Records and Archive preserve test memory without current authority. No test harness, test pass, test failure, benchmark, simulation, security scan, performance result, AI evaluation, dashboard test, connector test, secure-room test, public-safe publication test, Marketplace test, Studio test, teardown test, test record, retest, badge, report, dashboard, or archive creates recognition, certification, accreditation, audit opinion, public authority approval, procurement status, commercial approval, financeability, insurability, maturity certification, consent, deployment authorization, operational command, or execution authority by implication.**

## 67. Simulation-First Production

### 67.1 Simulation Logic

**67.1.1 Simulation-First Production Identity.** **Simulation-First Production** shall be the Foundry production discipline under which Nexus Foundry uses scenarios, models, synthetic environments, digital twins, stress tests, tabletop exercises, agent-based simulations, systems-dynamics models, infrastructure simulations, policy-learning simulations, disaster-risk simulations, finance-readable scenario maps, and controlled Studio runtime exercises before public-safe release, Marketplace listing, Registry status, Studio activation, National Portfolio use, Core Build presentation, Nexus Universe arena use, public authority learning, readiness mapping, support classification, lawful handoff preparation, or archive. Simulation shall be an upstream learning and review method; it shall not be a prediction authority, public warning system, public authority decision engine, finance determination, procurement decision, consent process, deployment authorization, or execution command.

**67.1.2 Simulation Purpose.** Simulation-First Production shall allow Foundry to examine possible behaviors, dependencies, stresses, risks, failure modes, second-order effects, safeguard implications, public authority learning questions, finance-readability questions, national portfolio conditions, data constraints, infrastructure fragilities, AI and agentic behaviors, Observatory signal behavior, dashboard interpretation, support burden, and teardown needs before real-world reliance is created. Simulation shall reduce preventable error by moving uncertainty into reviewable environments before release or continuation.

**67.1.3 Simulation as Evidence-Support, Not Evidence Replacement.** Simulation may support evidence formation by clarifying assumptions, revealing dependencies, testing mechanisms, stress-testing architecture, identifying risk pathways, and generating questions for further review. Simulation shall not replace source evidence, field validation, public authority judgment, community consent, Indigenous consent where applicable, legal permission, procurement process, finance process, insurance underwriting, deployment review, or lawful execution.

**67.1.4 Simulation Record.** Each material simulation shall have a **Simulation Record** identifying simulation purpose, scenario class, model or method, assumptions, variables, parameters, data inputs, synthetic data where used, excluded variables, uncertainty, sensitivity analysis where applicable, participating roles, environment, tool dependencies, AI involvement where applicable, digital twin relationship where applicable, public authority learning relevance, finance-readability relevance, safeguard relevance, national routing relevance, outputs, interpretation limits, reviewer, correction pathway, archive rule, and prohibited interpretations.

**67.1.5 Simulation Classes.** Simulation classes may include technical simulations, infrastructure simulations, climate and nature simulations, disaster-risk simulations, systems-risk simulations, cyber simulations, AI and agent simulations, Observatory simulations, digital twin simulations, National Portfolio simulations, public authority learning simulations, finance-readable scenario simulations, disaster risk finance simulations, public-safe communication simulations, Core Build simulations, Nexus Universe arena simulations, Studio runtime simulations, and handoff-dependency simulations.

**67.1.6 Simulation Sequence.** Simulation may occur during Intake, Backlog formation, Quest design, Bounty design, Build planning, Architecture Review, Data Review, AI Review, Cyber Review, Dual-Use Review, Public-Safe Review, National Portfolio preparation, Core Build preparation, Nexus Universe preparation, Studio runtime preparation, Marketplace and Registry preparation, readiness mapping, support planning, correction, renewal, sunsetting, teardown, and archive. Simulation shall be sequenced before irreversible public meaning or downstream reliance wherever practicable.

**67.1.7 Simulation Boundary.** Simulation performance, scenario result, digital twin output, stress-test result, finance-readable scenario, disaster-risk scenario, policy-learning output, public authority learning session, Studio simulation, Core Build simulation, Nexus Universe simulation, or simulation-derived dashboard shall not create forecast certainty, public warning, official classification, public authority approval, procurement status, financeability, insurability, maturity certification, community consent, Indigenous consent where applicable, deployment authorization, operational command, or execution authority.

**67.1.8 Simulation Correction.** Simulation Records shall be corrected where assumptions are wrong, data is stale, models drift, excluded variables become material, uncertainty is understated, outputs are overinterpreted, public-safe labels fail, public authority users treat simulation as decision, finance readers treat scenario as financeability, or simulation is used as deployment or execution evidence.

**67.1.9 Simulation Logic Formula.** Simulation-First Production shall operate according to the formula: **simulate before reliance; state assumptions before outputs; expose uncertainty before claims; convert scenarios into review questions; correct model drift; archive simulation memory; never let simulation become forecast certainty, public authority decision, finance approval, consent, deployment, or execution.**

***

### 67.2 Scenario Generation

**67.2.1 Scenario Generation Identity.** **Scenario Generation** shall be the governed process through which Foundry creates structured possible futures, stress conditions, disruption pathways, hazard combinations, stakeholder contexts, technology-change pathways, infrastructure states, policy settings, national portfolio conditions, public authority learning situations, finance-readable dependency cases, safeguard situations, and handoff conditions for use in simulation, review, learning, and planning.

**67.2.2 Scenario Generation Purpose.** Scenario Generation shall help Foundry ask better questions before building, releasing, publishing, listing, registering, demonstrating, supporting, or routing outputs. It shall reveal what must be tested, what assumptions are hidden, what data is missing, what stakeholders may be affected, what safeguards are needed, what public authority boundaries apply, what finance-readability questions arise, what national routing is required, what support capacity is needed, and what should not continue.

**67.2.3 Scenario Record.** Each material scenario shall have a Scenario Record identifying scenario title, purpose, domain, geography where applicable, time horizon, hazard or stressor class, technology class, affected systems, affected actors, assumptions, source records, data basis, uncertainty, excluded variables, public-safe class, safeguard class, public authority relevance, finance-readability relevance, national routing relevance, intended use, prohibited use, correction pathway, archive rule, and prohibited interpretations.

**67.2.4 Scenario Sources.** Scenario Generation may draw from Evidence Products, Observatory signals, DRI outputs, GRIx context, National Portfolio priorities, National Working Group inputs, Competence Cell insights, public authority learning questions, community inputs, Indigenous protocol inputs where applicable, academic literature, standards-interface materials, operational lessons, correction records, Core Build records, Nexus Universe outputs, public-safe reports, and lawful handoff dependency records.

**67.2.5 Scenario Types.** Scenarios may include baseline scenarios, stress scenarios, severe-but-plausible scenarios, compound-risk scenarios, low-probability high-impact scenarios, degraded-mode scenarios, technology-adoption scenarios, policy-change scenarios, infrastructure-failure scenarios, data-failure scenarios, cyber-risk scenarios, AI-failure scenarios, supply-chain scenarios, public authority learning scenarios, finance-readability scenarios, and non-continuation scenarios.

**67.2.6 Scenario Diversity.** Scenario sets shall avoid single-future thinking. Where material, Foundry shall generate contrasting scenarios, including successful continuation, partial failure, degraded performance, safeguard failure, public-safe misinterpretation, finance-readiness overclaim, national-routing delay, provider-dependency failure, public authority misunderstanding, and teardown failure.

**67.2.7 Scenario Boundary.** Scenario generation, scenario inclusion, scenario prioritization, scenario selection, or scenario discussion shall not create forecast, prediction, public warning, official classification, public authority decision, investment thesis, procurement priority, financeability, consent, deployment authorization, or execution authority.

**67.2.8 Scenario Correction.** Scenario Records shall be corrected where source assumptions change, affected actors are missed, national context changes, safeguards are incomplete, scenarios are framed as predictions, public authority users treat scenarios as decisions, or scenario selection is used as investment, procurement, or deployment signal.

**67.2.9 Scenario Generation Formula.** Scenario Generation shall follow the formula: **create structured possible futures from records; include uncertainty and alternatives; use scenarios to reveal questions and dependencies; correct scenario drift; never let scenario work become prediction, warning, investment signal, procurement signal, consent, deployment, or execution.**

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### 67.3 Multi-Hazard Simulation

**67.3.1 Multi-Hazard Simulation Identity.** **Multi-Hazard Simulation** shall be the governed simulation of interacting hazards, shocks, stresses, cascading failures, compound events, systemic risks, and cross-domain dependencies affecting people, infrastructure, ecosystems, technology systems, public authorities, National Portfolios, markets, supply chains, finance-readiness conditions, community safeguards, Indigenous protocols where applicable, and lawful handoff pathways.

**67.3.2 Multi-Hazard Simulation Purpose.** Multi-Hazard Simulation shall allow Foundry to examine how hazards combine rather than treating risk as isolated. It shall help identify cascading dependencies among climate, nature, water, energy, food, health, cyber, AI, compute, telecommunications, logistics, finance, governance, infrastructure, community vulnerability, public authority capacity, and technological systems.

**67.3.3 Multi-Hazard Simulation Record.** Each Multi-Hazard Simulation shall have a record identifying hazard classes, geography, time horizon, affected systems, affected actors, dependencies, data sources, assumptions, model or method, uncertainty, sensitivity, cascading pathways, compound effects, public-safe output class, safeguard relevance, national routing, public authority learning relevance, finance-readable relevance, reviewer, correction pathway, archive rule, and prohibited interpretations.

**67.3.4 Hazard Classes.** Hazard classes may include climate hazards, hydrological hazards, wildfire, heat, cold, storms, flooding, drought, seismic risk, nature and biodiversity stress, energy disruption, water system disruption, food system disruption, health system stress, cyber disruption, AI system failure, network disruption, compute failure, supply-chain disruption, infrastructure failure, social disruption, displacement, financial stress, and governance stress.

**67.3.5 Cascading Effects Review.** Multi-Hazard Simulation shall examine whether failure in one system affects other systems, including power-to-connectivity dependencies, connectivity-to-health dependencies, compute-to-public-authority learning dependencies, data-to-dashboard dependencies, infrastructure-to-finance-readiness dependencies, and community-safeguard-to-implementation dependencies.

**67.3.6 Safeguard and Public-Safe Controls.** Multi-Hazard outputs shall be reviewed for public-safe meaning, community harm, stigmatization, sensitive location exposure, protected knowledge exposure, Indigenous protocol sensitivity where applicable, public authority overclaim, finance overclaim, and panic or warning implication.

**67.3.7 Multi-Hazard Simulation Boundary.** Multi-Hazard Simulation output, risk pathway map, dashboard, scenario result, or stress-test result shall not create public warning, official risk classification, insurance determination, investment signal, procurement priority, public authority approval, consent, deployment authorization, operational command, or execution authority.

**67.3.8 Multi-Hazard Simulation Correction.** Records shall be corrected where hazard interactions are missed, assumptions become stale, cascading effects are overclaimed, uncertainty is hidden, public-safe language fails, sensitive geographies are exposed, or simulation outputs are used as warnings or ratings.

**67.3.9 Multi-Hazard Simulation Formula.** Multi-Hazard Simulation shall follow the formula: **simulate interacting hazards and cascading dependencies; label uncertainty and sensitivity; protect affected communities and places; convert results into review questions; never let hazard simulation become public warning, rating, finance signal, procurement signal, consent, deployment, or command.**

***

### 67.4 Digital Twin Simulation

**67.4.1 Digital Twin Simulation Identity.** **Digital Twin Simulation** shall be the governed use of digital twin models, virtual representations, geospatial models, infrastructure models, systems models, sensor-linked models, Observatory-linked models, synthetic environments, scenario environments, and Studio runtime environments to explore possible behavior of systems under recorded assumptions and constraints.

**67.4.2 Digital Twin Simulation Purpose.** Digital Twin Simulation shall support technical learning, infrastructure stress testing, Observatory interpretation, National Portfolio preparation, public authority learning, readiness mapping, safeguard assessment, Core Build demonstration, Nexus Universe arena work, Studio runtime interaction, and lawful handoff dependency identification. It shall not act as an operational control system by default.

**67.4.3 Digital Twin Simulation Record.** Each Digital Twin Simulation shall have a record identifying twin purpose, represented system, model boundaries, data sources, sensor links where applicable, update cadence, spatial resolution, temporal resolution, assumptions, excluded variables, uncertainty, validation status within scope, public-safe status, sensitivity class, access class, national routing, safeguard relevance, reviewer, correction pathway, archive rule, and prohibited interpretations.

**67.4.4 Data and Sensor Controls.** Digital Twin Simulation involving live or near-real-time sensor feeds, Edge telemetry, IoT, OT, AI-RAN/O-RAN-related telemetry, geospatial layers, infrastructure data, or community-sensitive data shall separate observation from command. Write-back, actuation, control, or operational command functions shall be disabled unless separately authorized outside default Foundry.

**67.4.5 Spatial and Infrastructure Sensitivity.** Digital Twin outputs shall be reviewed for sensitive locations, critical infrastructure exposure, cyber-sensitive topology, vulnerability exposure, community-sensitive places, protected knowledge, Indigenous-sensitive places or knowledge where applicable, public authority sensitivity, and public-safe display constraints.

**67.4.6 Digital Twin Validation.** Validation of a digital twin shall be scoped to model purpose, data availability, assumptions, calibration, uncertainty, and context. A digital twin validated for learning or simulation shall not be treated as validated for field operation, command, procurement, finance, insurance, public authority decision, or deployment.

**67.4.7 Digital Twin Simulation Boundary.** Digital Twin Simulation, model output, dashboard display, stress result, public authority learning session, Studio runtime, or Core Build demonstration shall not create public warning, operational control, official classification, public authority approval, procurement status, financeability, consent, deployment authorization, or execution authority.

**67.4.8 Digital Twin Simulation Correction.** Records shall be corrected where source data changes, sensor links fail, calibration changes, model assumptions drift, sensitive geographies are exposed, dashboards mislead, users treat the twin as operational control, or digital twin outputs are used as deployment evidence.

**67.4.9 Digital Twin Simulation Formula.** Digital Twin Simulation shall follow the formula: **model systems within recorded boundaries; separate simulation from control; protect sensitive spatial and infrastructure data; label uncertainty; correct model drift; never let digital twin output become command, approval, consent, deployment, or execution.**

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### 67.5 Policy Learning Simulation

**67.5.1 Policy Learning Simulation Identity.** **Policy Learning Simulation** shall be the governed use of scenarios, tabletop exercises, institutional simulations, decision-pathway simulations, public authority learning exercises, regulatory-interface exercises, procurement-neutral exercises, public finance relevance exercises, disaster governance exercises, and national portfolio exercises to help public authorities and related stakeholders understand dependencies, choices, risks, boundaries, and trade-offs without Foundry substituting for public authority decision-making.

**67.5.2 Policy Learning Simulation Purpose.** Policy Learning Simulation shall support learning by public authorities, National Councils, National Working Groups, universities, communities, providers, capital readers, and implementation actors about complex systems, risk pathways, infrastructure dependencies, public-good technologies, safeguards, data controls, national ownership, readiness dependencies, and lawful handoff conditions. It shall not produce official policy, regulation, procurement decision, budget allocation, public warning, public finance allocation, emergency command, permit, license, enforcement action, or legal approval.

**67.5.3 Policy Learning Simulation Record.** Each Policy Learning Simulation shall have a record identifying learning purpose, public authority context, jurisdiction, participants, scenario, assumptions, roles, materials used, decision points simulated, outputs, public authority boundary language, public-safe class, confidentiality class, finance or procurement sensitivity, safeguard relevance, national routing, reviewer, correction pathway, archive rule, and prohibited interpretations.

**67.5.4 Public Authority Boundary Controls.** Policy Learning Simulation shall state that the exercise is for learning, stress-testing, dependency identification, scenario exploration, and question formation only. Public authority participation, silence, questions, feedback, scenario choice, dashboard viewing, Studio interaction, or attendance shall not be represented as approval, adoption, policy position, procurement action, public finance action, or public authority decision.

**67.5.5 Policy Scenario Design.** Policy scenarios may address public authority coordination, degraded-mode governance, emergency logistics, data-sharing pathways, public-safe communication, risk observability, public-good technology adoption questions, procurement-neutral evaluation questions, legal dependencies, finance-readiness dependencies, and national capability formation.

**67.5.6 Outputs and Records.** Outputs may include learning notes, dependency maps, questions for competent authorities, public-safe summaries, correction items, readiness questions, safeguard conditions, national routing notes, and handoff dependency notes. Outputs shall not be framed as official conclusions unless separately issued by competent public authority.

**67.5.7 Policy Learning Simulation Boundary.** Policy Learning Simulation, tabletop output, public authority learning note, scenario result, dashboard interaction, Studio session, or public authority feedback shall not create public authority approval, public warning, official classification, procurement status, public finance allocation, regulatory comfort, policy adoption, consent, deployment authorization, emergency command, or execution authority.

**67.5.8 Policy Learning Simulation Correction.** Records and materials shall be corrected where public authority participation is overclaimed, learning notes are treated as decisions, dashboards imply official status, public-safe summaries imply warnings, or policy simulation outputs are used as procurement, finance, or deployment evidence.

**67.5.9 Policy Learning Simulation Formula.** Policy Learning Simulation shall follow the formula: **simulate policy choices for learning; record questions and dependencies; preserve public authority boundaries; correct decision overclaim; never let learning simulation become policy, approval, procurement, public finance, consent, deployment, or command.**

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### 67.6 Infrastructure Stress Testing

**67.6.1 Infrastructure Stress Testing Identity.** **Infrastructure Stress Testing** shall be the governed simulation, test, or exercise of infrastructure systems, technical architectures, network fabrics, compute environments, data rooms, secure rooms, Edge systems, Observatory nodes, dashboards, connectors, AI systems, Studio runtimes, National Dense Nexus Cores, regional clusters, Core Build environments, and related dependencies under load, disruption, degraded mode, failure, attack, scarcity, or recovery conditions.

**67.6.2 Infrastructure Stress Testing Purpose.** Infrastructure Stress Testing shall help Foundry understand fragility, capacity, failure modes, recovery options, degraded-mode behavior, dependency concentration, security exposure, support burden, national routing needs, and teardown requirements before infrastructure is used for public-safe release, Studio runtime, National Portfolio work, public authority learning, Core Build, Nexus Universe, readiness mapping, support, or handoff preparation.

**67.6.3 Infrastructure Stress Test Record.** Each stress test shall have a record identifying infrastructure object, environment, workload, stressor, failure condition, dependency assumptions, data class, cyber class, AI involvement where applicable, network conditions, compute conditions, storage conditions, recovery target where applicable, degraded-mode behavior, results, limitations, reviewer, correction pathway, archive rule, and prohibited interpretations.

**67.6.4 Stressor Classes.** Stressors may include high load, traffic surge, compute scarcity, GPU scarcity, network latency, network partition, storage exhaustion, cloud outage, power interruption, edge disconnection, data source loss, connector failure, API failure, model unavailability, cyber event, credential revocation, certificate expiration, dashboard overload, Studio surge, secure-room access failure, and teardown failure.

**67.6.5 Degraded-Mode Review.** Stress Testing shall review whether systems fail closed, fail safe, suppress unsafe outputs, preserve data controls, preserve public-safe labels, prevent unauthorized access, preserve Registry and Marketplace consistency, pause Studio runtime, withdraw dashboards, and notify appropriate stewards where needed.

**67.6.6 Infrastructure Stress and Public-Safe Output.** Stress-test results may be public-safe summarized only where disclosure does not expose vulnerabilities, infrastructure weaknesses, sensitive locations, cyber details, national-sensitive information, or provider-sensitive information. Public-safe summaries shall not imply operational readiness.

**67.6.7 Infrastructure Stress Testing Boundary.** Stress-test pass, resilience result, recovery result, degraded-mode result, Core Build infrastructure success, or Studio load success shall not create cybersecurity certification, infrastructure certification, public authority approval, procurement status, financeability, insurability, consent, deployment authorization, operational readiness, or execution authority.

**67.6.8 Infrastructure Stress Testing Correction.** Records shall be corrected where stress conditions are unrepresentative, recovery is overstated, vulnerabilities are exposed, degraded mode fails, support burden is understated, or stress-test success is used as deployment approval.

**67.6.9 Infrastructure Stress Testing Formula.** Infrastructure Stress Testing shall follow the formula: **stress systems before reliance; test failure and degraded modes; protect sensitive results; correct fragility; never let stress-test success become infrastructure certification, operational readiness, deployment authorization, or execution.**

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### 67.7 Finance-Readable Scenario Mapping

**67.7.1 Finance-Readable Scenario Mapping Identity.** **Finance-Readable Scenario Mapping** shall be the governed translation of simulation outputs, scenario dependencies, readiness questions, risk pathways, infrastructure needs, safeguard conditions, public authority dependencies, national routing needs, support obligations, and lawful handoff dependencies into forms that capital readers, insurers, donors, public finance actors, National Consortium Companies, Project SPVs, and lawful implementation actors can understand without treating those materials as investment advice, insurance advice, underwriting, donor approval, public finance approval, transaction readiness, valuation, solicitation, commitment, or financeability determination.

**67.7.2 Finance-Readable Scenario Mapping Purpose.** Finance-Readable Scenario Mapping shall make scenarios legible to capital and insurance readers while preserving finance-readiness without finance execution. It shall identify what questions a finance, insurance, donor, public finance, or enterprise actor would need to examine later through competent processes, without Foundry answering those questions as regulated determinations.

**67.7.3 Finance-Readable Scenario Mapping Record.** Each mapping shall have a record identifying scenario, simulation source, readiness question, dependency class, public authority dependency, legal dependency, procurement dependency, finance or insurance dependency, donor or public finance dependency, data dependency, cyber dependency, AI dependency where applicable, safeguard dependency, national routing, support dependency, assumptions, no-reliance language, reviewer, correction pathway, archive rule, and prohibited interpretations.

**67.7.4 Mapping Outputs.** Outputs may include dependency maps, risk-to-capital question maps, insurance-readable question maps, donor-readiness question maps, public finance relevance notes, SPV-readiness notes, National Consortium Company continuation notes, handoff dependency notes, and no-reliance scenario summaries. Outputs shall be framed as questions and dependencies, not determinations.

**67.7.5 No-Reliance Controls.** Finance-readable scenario materials shall include no-reliance, non-advisory, non-soliciting, non-transactional, non-underwriting, non-commitment, non-rating, non-valuation, competition-compliant, confidentiality-aware, and regulated-perimeter language as appropriate to audience and risk.

**67.7.6 Capital-Reader Participation.** Capital-reader, insurer, donor, public finance, or enterprise participation in scenario mapping shall be recorded as learning, reading, question formation, or dependency review only. Presence, feedback, or questions shall not be represented as investment interest, underwriting interest, donor interest, public finance interest, transaction interest, or approval.

**67.7.7 Finance-Readable Scenario Boundary.** Finance-readable scenario mapping, no-reliance notes, capital-reader materials, insurance-readable materials, donor/public finance relevance materials, or SPV-readiness questions shall not create financeability, bankability, investability, insurability, underwriting acceptance, donor approval, public finance approval, investment advice, securities advice, valuation, procurement status, consent, deployment authorization, or execution authority.

**67.7.8 Finance-Readable Scenario Correction.** Records and materials shall be corrected where readiness language overclaims, no-reliance language is missing, scenario outputs are framed as determinations, capital-reader presence is overstated, insurance relevance is treated as insurability, donor relevance is treated as donor approval, or public finance relevance is treated as allocation.

**67.7.9 Finance-Readable Scenario Mapping Formula.** Finance-Readable Scenario Mapping shall follow the formula: **translate scenarios into dependency questions; preserve no-reliance; separate readability from finance; correct transaction implication; never let scenario mapping become investment, insurance, donor, public finance, procurement, consent, deployment, or execution.**

***

### 67.8 Disaster Risk Finance Simulation Support

**67.8.1 Disaster Risk Finance Simulation Support Identity.** **Disaster Risk Finance Simulation Support** shall be the governed Foundry support for simulations, scenarios, stress tests, readiness questions, observability inputs, dependency maps, and public-safe materials that help stakeholders understand disaster risk finance dependencies, protection gaps, contingent finance questions, insurance-readability questions, public finance relevance, donor relevance, resilience investment dependencies, and National Portfolio implications without Foundry acting as insurer, reinsurer, broker, underwriter, lender, investment adviser, donor allocator, public finance allocator, guarantee provider, rating agency, or transaction platform.

**67.8.2 Disaster Risk Finance Simulation Purpose.** Disaster Risk Finance Simulation Support shall help convert disaster-risk scenarios into structured learning about exposure, vulnerability, resilience needs, data gaps, public authority dependencies, protection-gap questions, insurance-readiness dependencies, risk-layering questions, fiscal-risk questions, donor/public finance relevance, safeguard needs, and lawful handoff dependencies. It shall support readability, not finance execution.

**67.8.3 Disaster Risk Finance Simulation Record.** Each simulation support activity shall have a record identifying disaster scenario, hazard class, geography, affected systems, affected actors, exposure assumptions, vulnerability assumptions, data sources, public authority relevance, insurance relevance, donor/public finance relevance, national routing, safeguard conditions, uncertainty, limitation, no-reliance language, reviewer, correction pathway, archive rule, and prohibited interpretations.

**67.8.4 Simulation Support Outputs.** Outputs may include disaster-risk scenario maps, dependency maps, protection-gap question maps, data-gap notes, resilience-readiness notes, insurance-readable questions, public finance relevance notes, donor relevance notes, public authority learning notes, National Portfolio notes, and handoff dependency notes.

**67.8.5 Insurance and Finance Boundary.** Disaster Risk Finance Simulation Support shall not price risk, underwrite risk, rate risk, recommend insurance, recommend investment, advise public finance allocation, determine eligibility, issue guarantee opinions, assess bankability, determine financeability, create transaction readiness, or provide regulated financial advice.

**67.8.6 Public-Safe Disaster Communication.** Disaster-risk simulation outputs shall be reviewed to avoid public warning implication, panic, false certainty, community stigmatization, insurance implication, investment implication, public authority overclaim, and sensitive location exposure. Outputs shall use uncertainty and limitation statements.

**67.8.7 Disaster Risk Finance Simulation Boundary.** Disaster Risk Finance Simulation Support, scenario output, protection-gap note, insurance-readable question, public finance relevance note, donor relevance note, or resilience-readiness map shall not create insurance approval, financeability, bankability, investment advice, underwriting acceptance, donor approval, public finance allocation, public warning, public authority approval, consent, deployment authorization, or execution authority.

**67.8.8 Disaster Risk Finance Simulation Correction.** Records and materials shall be corrected where risk is overstated, uncertainty is hidden, public warning implication appears, insurance language overclaims, finance language overclaims, public finance relevance is treated as allocation, or community vulnerability is exposed unsafely.

**67.8.9 Disaster Risk Finance Simulation Formula.** Disaster Risk Finance Simulation Support shall follow the formula: **simulate disaster-risk dependencies for learning; translate exposure and vulnerability into questions; preserve no-reliance and public-safe limits; correct finance and warning overclaim; never let disaster-risk simulation become underwriting, finance, public warning, consent, deployment, or execution.**

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### 67.9 Simulation Uncertainty Statements

**67.9.1 Uncertainty Statement Identity.** **Simulation Uncertainty Statements** shall be required explanatory records and labels accompanying material simulations, scenarios, digital twins, stress tests, policy-learning simulations, finance-readable scenario mappings, disaster-risk simulations, dashboards, public-safe summaries, Studio runtimes, Core Build outputs, Nexus Universe materials, National Portfolio materials, and handoff dependency notes where outputs could be misread as predictions, decisions, ratings, or approvals.

**67.9.2 Uncertainty Statement Purpose.** Uncertainty Statements shall ensure that users understand what is known, unknown, assumed, excluded, estimated, modeled, synthetic, incomplete, time-bound, environment-bound, data-bound, jurisdiction-bound, support-bound, and non-transferable. They shall prevent simulation outputs from becoming false certainty.

**67.9.3 Uncertainty Statement Record.** Each Uncertainty Statement shall identify simulation or scenario, model or method, data sources, assumptions, excluded variables, uncertainty sources, sensitivity conditions, confidence where appropriate, limitations, non-transferability, review date, public-safe status, correction pathway, archive rule, and prohibited interpretations.

**67.9.4 Required Uncertainty Elements.** Uncertainty Statements shall include:\
67.9.4(a) what the simulation is designed to explore;\
67.9.4(b) what it is not designed to determine;\
67.9.4(c) data sources and known limitations;\
67.9.4(d) assumptions and excluded variables;\
67.9.4(e) sensitivity to parameter changes where material;\
67.9.4(f) environment and version limits;\
67.9.4(g) audience and use limits;\
67.9.4(h) no-forecast, no-warning, no-approval, no-finance, no-procurement, no-consent, no-deployment, and no-execution meaning where applicable.

**67.9.5 Visual Uncertainty Labels.** Dashboards, maps, charts, Studio outputs, digital twin views, and public-safe summaries shall display uncertainty visibly where reliance risk exists. Visual design shall not hide uncertainty through false precision, color intensity, ranking, thresholds, or alarm-like design.

**67.9.6 Uncertainty and Public-Safe Publication.** Public-safe materials shall translate uncertainty into understandable language without oversimplifying or removing boundary meaning. Plain-language communication shall not become false confidence.

**67.9.7 Uncertainty Statement Boundary.** An Uncertainty Statement shall not cure an otherwise unsafe or overclaimed output. Where uncertainty is too high, sensitivity is unsafe, or public meaning is likely to mislead, Foundry may restrict, revise, withdraw, or archive the output rather than publish it with a disclaimer.

**67.9.8 Uncertainty Statement Correction.** Uncertainty Statements shall be corrected where assumptions change, data changes, models change, sensitivity changes, public understanding changes, uncertainty is understated, or outputs are used as predictions or approvals.

**67.9.9 Simulation Uncertainty Formula.** Simulation Uncertainty Statements shall follow the formula: **state purpose, assumptions, exclusions, limits, sensitivity, and non-transferability; make uncertainty visible; restrict outputs where uncertainty cannot be safely communicated; never let uncertainty language become permission to overclaim.**

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### 67.10 Simulation Without Forecast Certainty or Public Authority Decision

**67.10.1 No Forecast Certainty Rule.** **Simulation Without Forecast Certainty or Public Authority Decision** shall be the controlling rule that no Foundry simulation, scenario, digital twin, stress test, policy-learning simulation, disaster-risk simulation, finance-readable scenario map, dashboard, Studio runtime, public-safe summary, Core Build output, Nexus Universe output, National Portfolio material, or handoff dependency note shall be represented as certain prediction, official forecast, public warning, official risk classification, policy decision, regulatory decision, procurement decision, public finance decision, emergency command, consent record, deployment authorization, or execution command.

**67.10.2 Purpose.** This rule shall preserve simulation as learning infrastructure. It shall allow Foundry to explore uncertainty rigorously without pretending to replace competent public authority, legal authority, procurement authority, financial authority, insurance authority, community consent authority, Indigenous consent authority where applicable, operational authority, or implementation authority.

**67.10.3 Required Boundary Language.** Simulation outputs shall include boundary language appropriate to audience and risk, stating that simulation is exploratory, assumption-bound, context-bound, time-bound, data-bound, model-bound, and subject to correction. Where relevant, materials shall state no public warning, no official classification, no public authority approval, no procurement effect, no finance or insurance effect, no donor or public finance effect, no consent effect, no deployment authorization, and no execution authority.

**67.10.4 Public Authority Context.** Where public authorities participate, view, discuss, or receive simulation outputs, their participation shall be described as learning, exploration, dependency review, scenario discussion, or question formation only. Foundry shall not state or imply that a public authority accepted, approved, adopted, endorsed, or acted upon simulation outputs unless separately and lawfully recorded by that public authority.

**67.10.5 Public Communication.** Public communication of simulation results shall be carefully controlled. Foundry shall not publish simulation outputs in a manner likely to be read as emergency warning, official forecast, rating, public safety instruction, public authority decision, insurance determination, investment signal, procurement recommendation, or deployment instruction.

**67.10.6 Operational Separation.** Simulation environments shall be separated from operational control systems by default. Dashboards, digital twins, agents, or Studio runtimes used for simulation shall not actuate systems, command operations, change public authority records, update finance records, execute procurement, or trigger implementation unless separately authorized outside default Foundry.

**67.10.7 Boundary Effect.** Compliance with this rule shall not prevent simulation outputs from informing evidence products, readiness questions, public authority learning, National Portfolio preparation, safeguard review, support planning, or lawful handoff dependency mapping. It only prevents simulation outputs from being treated as external decision authority.

**67.10.8 Boundary Correction.** Materials, records, dashboards, Studio outputs, public-safe summaries, and participant communications shall be corrected where simulation is overclaimed as forecast, warning, approval, financeability, procurement suitability, consent, deployment authorization, or execution authority.

**67.10.9 No Forecast Certainty Formula.** Simulation Without Forecast Certainty or Public Authority Decision shall follow the formula: **simulate to learn, not to decide; state boundaries visibly; separate simulation from operations; correct forecast and authority overclaim; never let simulation become warning, policy, procurement, finance, consent, deployment, or execution.**

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### 67.11 Simulation-to-Evidence Conversion

**67.11.1 Simulation-to-Evidence Conversion Identity.** **Simulation-to-Evidence Conversion** shall be the governed process through which simulation outputs may be translated into Evidence Products, Evidence Notes, Readiness Questions, Safeguard Notes, Public Authority Learning Records, National Portfolio inputs, Studio learning records, Observatory learning records, Core Build learning records, Nexus Universe outputs, correction items, support items, and handoff dependency questions.

**67.11.2 Conversion Purpose.** Simulation-to-Evidence Conversion shall ensure that simulation results are used appropriately: as structured evidence-support, hypothesis generation, dependency discovery, failure-mode discovery, sensitivity analysis, learning record, or review input. It shall prevent simulation outputs from being converted directly into conclusions, approvals, certifications, public warnings, finance determinations, procurement recommendations, consent records, deployment authorizations, or execution commands.

**67.11.3 Conversion Record.** Each material conversion shall have a Simulation-to-Evidence Conversion Record identifying source simulation, output being converted, evidence claim proposed, conversion class, assumptions retained, uncertainty retained, limitations retained, source records, reviewer, evidence status, public-safe status, safeguard relevance, national routing, readiness relevance, correction pathway, archive rule, and prohibited interpretations.

**67.11.4 Conversion Classes.** Conversion classes may include hypothesis, evidence question, dependency note, failure-mode note, sensitivity note, public authority learning note, readiness question, finance-readable question, safeguard note, support note, correction item, design requirement, test requirement, documentation update, dashboard label update, Studio update, Registry note, Marketplace note, or handoff dependency note.

**67.11.5 Evidence Threshold.** Simulation output shall not become evidence claim unless the Evidence Review confirms scope, source basis, method, assumptions, limitations, uncertainty, and appropriate use. Where simulation only generates a question, it shall remain a question.

**67.11.6 Public-Safe Conversion.** Public-safe materials derived from simulation shall preserve uncertainty, assumptions, limits, and no-conversion language. Simplified summaries shall not transform scenario exploration into forecast or official status.

**67.11.7 Conversion Boundary.** Simulation-to-Evidence Conversion shall not create scientific consensus, certification, public authority approval, procurement status, financeability, insurability, maturity status, consent, deployment authorization, operational command, or execution authority. Conversion creates bounded evidence-support records only.

**67.11.8 Conversion Correction.** Conversion Records shall be corrected where simulation assumptions are lost, uncertainty is omitted, scenario outputs are treated as facts, evidence claims exceed support, public-safe summaries overclaim, or conversion is used as approval or deployment evidence.

**67.11.9 Simulation-to-Evidence Formula.** Simulation-to-Evidence Conversion shall follow the formula: **convert outputs into questions, dependencies, and bounded evidence-support; retain assumptions and uncertainty; require Evidence Review; correct conversion overclaim; never let simulation output become conclusion, approval, consent, deployment, or execution.**

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### 67.12 Simulation Archive

**67.12.1 Simulation Archive Identity.** The **Simulation Archive** shall be the governed memory surface for simulation records, scenario records, model versions, assumptions, parameters, input data references, synthetic datasets, output records, uncertainty statements, review records, public-safe summaries, correction records, dashboard snapshots, Studio session records, Core Build simulation records, Nexus Universe simulation records, National Portfolio simulation records, finance-readable scenario records, disaster-risk simulation records, support records, withdrawal records, and non-continuation records.

**67.12.2 Simulation Archive Purpose.** The Simulation Archive shall preserve institutional learning without preserving forecast authority or current decision status. It shall allow Foundry to understand what was simulated, why it was simulated, what assumptions were used, what uncertainty existed, what was learned, what was corrected, what was withdrawn, what was archived, and what future use is restricted.

**67.12.3 Simulation Archive Record.** Each archived simulation shall have an Archive Record identifying simulation, scenario, model or method, version, active period, source records, data class, sensitivity class, assumptions, outputs, uncertainty statements, review history, correction history, public-safe release history, dashboard history, Studio history, National Portfolio relationship, public authority learning relationship, finance-readability relationship, handoff relationship where applicable, access restrictions, retention rule, deletion or sealing rule where applicable, reinstatement conditions, future-use restrictions, and prohibited interpretations.

**67.12.4 Archive Classes.** Simulation Archive classes may include public archive, controlled archive, restricted archive, secure archive, national archive, public authority learning archive, finance-readable archive, disaster-risk archive, Studio archive, Core Build archive, Nexus Universe archive, National Portfolio archive, correction archive, sealed archive, deletion-verified archive, and non-continuation archive.

**67.12.5 Archive Access Discipline.** Archive access shall be governed by data sensitivity, model sensitivity, cyber sensitivity, infrastructure sensitivity, geospatial sensitivity, public authority sensitivity, community sensitivity, Indigenous protocol sensitivity where applicable, protected knowledge restrictions, finance-reader confidentiality, provider confidentiality, sponsor confidentiality, national routing, and public-safe rules.

**67.12.6 Archive Without Current Authority.** Archived simulations shall not be cited as current evidence, current forecast, current risk classification, current public authority learning output, current finance-readable mapping, current National Portfolio basis, current handoff basis, current Studio runtime, current dashboard, public warning, public authority decision, consent, deployment authorization, or execution authority unless reinstated by current review and record.

**67.12.7 Reuse and Reinstatement.** Reuse of archived simulations shall require review of source validity, model validity, assumptions, data permission, sensitivity, uncertainty, public-safe meaning, national routing, safeguard conditions, support status, and intended audience. Copying an old model, rerunning an old notebook, relinking a dashboard, or presenting an old scenario shall not reinstate current status.

**67.12.8 Simulation Archive Correction.** Simulation Archive Records shall be corrected where archive class is wrong, assumptions are missing, sensitivity changes, public-safe summaries are misused, old outputs are cited as current, archived dashboards remain accessible, or simulation archive is used as forecast or approval.

**67.12.9 Final Simulation-First Production Formula.** The controlling Simulation-First Production Formula is that **Simulation Logic makes simulation an upstream learning and review method; Scenario Generation creates structured possible futures without prediction; Multi-Hazard Simulation examines interacting risks without warning authority; Digital Twin Simulation models systems without operational command; Policy Learning Simulation supports public authority learning without public authority substitution; Infrastructure Stress Testing examines fragility without infrastructure certification; Finance-Readable Scenario Mapping translates dependencies without finance execution; Disaster Risk Finance Simulation Support supports risk-finance readability without underwriting or allocation; Simulation Uncertainty Statements make assumptions and limits visible; Simulation Without Forecast Certainty or Public Authority Decision preserves learning without decision authority; Simulation-to-Evidence Conversion turns outputs into bounded evidence-support only after review; and Simulation Archive preserves institutional memory without current authority. No simulation, scenario, digital twin, stress test, policy-learning exercise, finance-readable map, disaster-risk simulation, uncertainty statement, simulation dashboard, Studio simulation, Core Build simulation, Nexus Universe simulation, public authority learning output, National Portfolio simulation, evidence conversion, archive record, or public-safe summary creates forecast certainty, public warning, official classification, public authority approval, procurement status, financeability, insurability, maturity certification, community consent, Indigenous consent where applicable, deployment authorization, operational command, or execution authority by implication.**

## 68. Evidence Products

### 68.1 Evidence Pack

**68.1.1 Evidence Pack Identity.** An **Evidence Pack** shall be a governed, record-bearing, source-grounded, method-bounded, reviewable, public-safe where applicable, correctionable, and archive-ready Foundry Evidence Product that assembles the evidence needed to support a defined Foundry question, Product Line, Pack, Rail, Dashboard, Observatory output, DRI output, Readiness Product, Safeguard Product, National Portfolio object, Studio Runtime Package, Marketplace description, Registry record, Core Build output, Nexus Universe output, public authority learning material, or lawful handoff dependency package. An Evidence Pack shall organize what is known, how it is known, what remains uncertain, what cannot be claimed, and what downstream uses are prohibited.

**68.1.2 Evidence Pack Purpose.** Evidence Packs shall prevent Foundry claims from being built on informal memory, unsupported summaries, provider materials alone, sponsor narratives, AI-generated text, event impressions, unreviewed dashboards, untraceable datasets, or undocumented simulations. They shall convert fragmented records into reviewable evidence without turning evidence organization into certification, public authority approval, financeability, procurement status, consent, deployment authorization, or execution authority.

**68.1.3 Evidence Pack Record.** Each Evidence Pack shall have an **Evidence Pack Record** identifying Evidence Pack title, purpose, evidence question, object or Product Line supported, source records, datasets, methods, assumptions, uncertainty, limitations, evidence gaps, model involvement where applicable, AI involvement where applicable, simulation involvement where applicable, benchmark involvement where applicable, public-safe class, safeguard class, national routing relevance, public authority relevance, finance-readability relevance, support status, reviewer, correction pathway, archive rule, and prohibited interpretations.

**68.1.4 Evidence Pack Components.** An Evidence Pack may include Method Notes, Dataset Records, Model Cards, System Cards, Benchmark Records, Compute-Use Records, Network Performance Records, DRI Records, Observatory Records, Proof Records, Public-Safe Evidence Summaries, Simulation Records, Review Records, Correction Records, and Archive Records. Components shall remain individually traceable and shall not be collapsed into a single unsupported conclusion.

**68.1.5 Evidence Pack Classes.** Evidence Packs may be technical, observational, methodological, data-oriented, AI-oriented, cyber-oriented, infrastructure-oriented, dashboard-oriented, public-safe, safeguard-oriented, readiness-oriented, finance-readable, public-authority-learning, national-portfolio, Core Build, Nexus Universe, Marketplace, Registry, Studio, handoff-dependency, correction, renewal, sunsetting, or archive Evidence Packs.

**68.1.6 Evidence Pack Claims Discipline.** Evidence Packs shall distinguish verified record, reviewed evidence, model output, simulation output, inference, assumption, expert judgment, stakeholder input, public authority learning input, capital-reader question, community input, Indigenous protocol input where applicable, and unresolved dependency. Evidence Packs shall not state conclusions broader than the evidence supports.

**68.1.7 Evidence Pack Boundary.** Evidence Pack creation, review, completeness, publication, Registry reference, Marketplace reference, Studio use, National Portfolio use, Core Build use, Nexus Universe use, public authority learning use, or handoff-dependency use shall not create scientific consensus, certification, public authority approval, procurement status, financeability, insurability, maturity certification, consent, deployment authorization, operational command, or execution authority.

**68.1.8 Evidence Pack Correction.** Evidence Packs shall be corrected where sources change, methods are flawed, uncertainty is understated, datasets become stale, model behavior changes, simulations are overinterpreted, public-safe summaries overclaim, safeguards are incomplete, national routing is missed, or Evidence Pack status is used as approval or deployment evidence.

**68.1.9 Evidence Pack Formula.** Evidence Packs shall follow the formula: **assemble evidence by record; separate fact, inference, method, model, scenario, and judgment; state uncertainty and gaps; review before use; correct evidence drift; archive non-current evidence; never let evidence organization become certification, finance, procurement, consent, deployment, or execution.**

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### 68.2 Method Note

**68.2.1 Method Note Identity.** A **Method Note** shall be a governed Evidence Product that describes the method, procedure, analytical pathway, simulation logic, data treatment, review process, benchmark design, dashboard calculation, AI evaluation approach, public-safe review method, safeguard review method, readiness mapping method, or proof-generation method used in Foundry work.

**68.2.2 Method Note Purpose.** Method Notes shall make Foundry methods understandable, reviewable, reproducible where appropriate, bounded, and correctionable. They shall prevent methods from becoming hidden authority, undocumented institutional custom, unreviewed expert judgment, provider-shaped process, sponsor-shaped process, or AI-generated procedure without human review.

**68.2.3 Method Note Record.** Each Method Note shall have a Method Note Record identifying method name, purpose, object class supported, source records, steps, assumptions, inputs, outputs, exclusions, required competencies, tools, data requirements, AI involvement where applicable, cyber or secure-room requirements where applicable, public-safe implications, safeguard implications, validation status within scope, limitations, reviewer, correction pathway, archive rule, and prohibited interpretations.

**68.2.4 Method Note Classes.** Method Notes may include evidence methods, data methods, Observatory methods, DRI methods, dashboard methods, benchmark methods, simulation methods, AI evaluation methods, cyber review methods, public-safe publication methods, safeguard methods, readiness mapping methods, finance-readable mapping methods, National Portfolio methods, Studio runtime methods, Marketplace review methods, Registry state methods, and handoff-dependency methods.

**68.2.5 Method Transparency.** Method Notes shall state what the method can support and what it cannot support. A method used for learning shall not be described as a method for approval. A method used for simulation shall not be described as a method for forecasting. A method used for readiness mapping shall not be described as a method for financeability, procurement, or deployment authorization.

**68.2.6 Method Reuse.** Method Notes may support repeatability across Product Lines, National Nodes, Competence Cells, Academy pathways, Marketplace objects, Registry states, Studio runtimes, Core Build cycles, and Nexus Universe outputs, provided that context-specific limits, national localization, safeguards, data controls, and support status remain recorded.

**68.2.7 Method Note Boundary.** Method Note publication, use, review, reuse, Registry reference, Marketplace reference, Studio use, or National Portfolio use shall not create methodological certification, legal sufficiency, scientific consensus, public authority approval, procurement status, financeability, consent, deployment authorization, or execution authority.

**68.2.8 Method Note Correction.** Method Notes shall be corrected where steps are incomplete, assumptions are wrong, tools change, AI involvement changes, data requirements change, validation is overstated, national localization changes meaning, or the method is used as approval.

**68.2.9 Method Note Formula.** Method Notes shall follow the formula: **document how work is done; state assumptions, inputs, outputs, and limits; review methods before reuse; correct method drift; never let method discipline become certification, approval, finance, procurement, consent, deployment, or execution.**

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### 68.3 Dataset Record

**68.3.1 Dataset Record Identity.** A **Dataset Record** shall be a governed Evidence Product documenting a dataset, data source, data extract, derived dataset, synthetic dataset, aggregate dataset, geospatial layer, sensor feed, Observatory input, dashboard input, AI input where permitted, public-safe output dataset, secure-room dataset, data-room dataset, compute-to-data output, or archive dataset used in Foundry.

**68.3.2 Dataset Record Purpose.** Dataset Records shall make data provenance, classification, custody, residency, permission, quality, limitations, AI-use conditions, output-review obligations, retention, deletion, sealing, archive, and correction visible before data is used in evidence, dashboards, simulations, Observatory work, DRI work, AI workflows, Studio runtimes, Marketplace materials, Registry records, National Portfolio materials, public-safe summaries, or handoff dependency packages.

**68.3.3 Dataset Record Elements.** Each Dataset Record shall identify dataset title, source, steward or custodian, version, date range, geography where applicable, data class, sensitivity class, provenance, collection method, processing method, metadata status, data dictionary status, quality notes, missingness, uncertainty, residency, access rules, permitted uses, prohibited uses, AI-use rule, output-review rule, retention rule, deletion or sealing rule, public-safe status, correction pathway, archive rule, and prohibited interpretations.

**68.3.4 Dataset Classes.** Dataset classes may include public-safe dataset, controlled dataset, restricted dataset, confidential dataset, national-only dataset, sovereign-sensitive dataset, public authority-sensitive dataset, community-sensitive dataset, Indigenous-sensitive dataset where applicable, protected knowledge dataset, health-sensitive dataset, infrastructure-sensitive dataset, cyber-sensitive dataset, legal-sensitive dataset, synthetic dataset, aggregate dataset, derived dataset, no-download dataset, compute-to-data dataset, secure-room dataset, archive-only dataset, and deletion-verified dataset.

**68.3.5 Dataset Quality and Limitations.** Dataset Records shall state quality constraints, including missing data, inconsistent fields, uncertain provenance, stale records, sampling limitations, measurement error, geospatial precision limits, sensor drift, transformation limits, aggregation limits, privacy limits, and public-safe limits. Data quality shall not be overstated as truth.

**68.3.6 Dataset and AI Controls.** Dataset Records shall explicitly state whether the dataset may be used for AI retrieval, embeddings, summarization, translation, classification, training, fine-tuning, agent workflows, output generation, or model evaluation. No AI use shall be implied merely because the dataset is accessible.

**68.3.7 Dataset Record Boundary.** Dataset Record creation, data-quality note, metadata completeness, access approval for a data room, secure-room use, public-safe aggregate, or Dataset Record publication shall not create data ownership, unrestricted use rights, publication permission, AI training permission, public authority approval, procurement status, financeability, consent, deployment authorization, or execution authority.

**68.3.8 Dataset Record Correction.** Dataset Records shall be corrected where classification is wrong, provenance changes, permission changes, residency is misstated, data quality changes, AI-use rules are wrong, derived copies are untracked, public-safe outputs expose sensitivity, or Dataset Record status is treated as permission.

**68.3.9 Dataset Record Formula.** Dataset Records shall follow the formula: **record source, custody, classification, quality, permission, AI limits, retention, and output review; correct data drift; archive or delete by rule; never let data documentation become data ownership, consent, deployment, or execution authority.**

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### 68.4 Model Card

**68.4.1 Model Card Identity.** A **Model Card** shall be a governed Evidence Product documenting an AI model, statistical model, forecasting model, simulation model, geospatial model, classification model, optimization model, digital twin model, DRI model, Observatory model, benchmark model, or other model used by Foundry to support analysis, simulation, dashboarding, AI workflow, evidence generation, Studio runtime, public-safe publication, readiness mapping, or handoff dependency mapping.

**68.4.2 Model Card Purpose.** Model Cards shall make model purpose, provenance, version, assumptions, training or calibration context where known and appropriate, inputs, outputs, evaluation, limitations, risks, bias or harm concerns where relevant, uncertainty, data constraints, AI-use rules, public-safe limits, support status, correction triggers, and archive rules visible before model outputs are relied upon within Foundry.

**68.4.3 Model Card Record.** Each Model Card shall identify model name, version, provider or steward, model type, purpose, intended use, prohibited use, input classes, output classes, training or calibration basis where available and appropriate, data dependencies, evaluation results, benchmark results where applicable, uncertainty, limitations, known failure modes, bias or harm considerations where relevant, security considerations, public-safe status, support status, update rule, correction pathway, archive rule, and prohibited interpretations.

**68.4.4 Model Classes.** Model classes may include language model, vision model, geospatial model, climate model, disaster-risk model, infrastructure model, digital twin model, systems-dynamics model, agent-based model, statistical model, classification model, optimization model, DRI model, risk-index model, benchmark model, simulation model, and public-safe summarization model.

**68.4.5 Model Use Limits.** Model Cards shall state whether model outputs are allowed for draft support, review support, analysis support, restricted use, public-safe candidate use, dashboard support, Studio runtime, public authority learning, finance-readable scenario mapping, National Portfolio preparation, or handoff dependency support. Model output shall not be used beyond its recorded scope.

**68.4.6 Model Evaluation.** Model Cards shall identify evaluations performed, evaluation environment, test data, limitations, red-team findings where applicable, human review, failure modes, drift risks, and retesting triggers. Evaluation shall not be represented as AI safety certification or universal validation.

**68.4.7 Model Card Boundary.** Model Card completion, model evaluation, benchmark result, public-safe use, Studio use, Registry reference, Marketplace reference, or National Portfolio use shall not certify AI safety, model validity for all contexts, legal compliance, public authority approval, procurement status, financeability, consent, deployment authorization, operational command, or execution authority.

**68.4.8 Model Card Correction.** Model Cards shall be corrected where model version changes, provider terms change, training or calibration basis changes, evaluation is stale, outputs drift, failure modes emerge, data permissions change, public-safe limits change, or Model Card status is used as certification.

**68.4.9 Model Card Formula.** Model Cards shall follow the formula: **record model purpose, provenance, version, evaluation, limits, and failure modes; restrict use by scope; retest on drift; correct model claims; never let a Model Card become AI certification, approval, consent, deployment, or execution.**

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### 68.5 System Card

**68.5.1 System Card Identity.** A **System Card** shall be a governed Evidence Product documenting a system composed of multiple components, including software, models, agents, connectors, dashboards, data pipelines, compute environments, network pathways, secure rooms, data rooms, Studio runtimes, Marketplace surfaces, Registry integrations, Observatory systems, DRI systems, Deployment Units, or National Portfolio systems.

**68.5.2 System Card Purpose.** System Cards shall make system purpose, architecture, components, dependencies, data flows, control boundaries, AI involvement, cyber controls, public-safe status, safeguards, national routing, support status, reliability, limitations, correction triggers, teardown obligations, and archive rules visible before a system is released, listed, registered, Studio-activated, demonstrated, supported, or handoff-adjacent.

**68.5.3 System Card Record.** Each System Card shall identify system name, version, purpose, object class, architecture summary, components, component versions, dependencies, providers, open baseline components, proprietary components, data flows, compute environment, network environment, storage environment, AI systems, agent permissions, access rules, security controls, public-safe controls, safeguard controls, support class, reliability assumptions, teardown plan, correction pathway, archive rule, and prohibited interpretations.

**68.5.4 System Classes.** System Cards may apply to Observatory systems, dashboard systems, Studio runtime systems, secure-room systems, data-room systems, AI agent systems, Registry systems, Marketplace systems, National Portfolio systems, Core Build systems, Nexus Universe systems, public-safe publication systems, and lawful handoff-preparation systems.

**68.5.5 System Boundary Mapping.** System Cards shall identify what the system does and does not do, including whether it reads data, writes data, updates records, displays dashboards, routes workflows, generates outputs, uses AI, connects to external systems, supports public authority learning, supports finance-readability, or supports handoff dependency mapping. Operational control shall not be implied.

**68.5.6 System Risk and Support.** System Cards shall identify known risks, dependency risks, support burden, degraded-mode behavior, security risks, AI risks, data risks, public-safe risks, safeguard risks, national routing risks, provider dependencies, and teardown risks. Support shall be classified by record.

**68.5.7 System Card Boundary.** System Card completion, architecture documentation, release candidate status, Registry reference, Marketplace listing, Studio activation, Core Build demonstration, Nexus Universe demonstration, or National Portfolio relationship shall not create certification, public authority approval, procurement status, financeability, maturity certification, consent, deployment authorization, operational readiness, or execution authority.

**68.5.8 System Card Correction.** System Cards shall be corrected where components change, dependencies change, data flows change, AI permissions change, support changes, public-safe meaning changes, safeguards change, national routing changes, or System Card status is used as deployment approval.

**68.5.9 System Card Formula.** System Cards shall follow the formula: **document composed systems, dependencies, data flows, controls, support, limits, and teardown; correct system drift; archive non-current systems; never let system documentation become certification, deployment authorization, or execution.**

***

### 68.6 Benchmark Record

**68.6.1 Benchmark Record Identity.** A **Benchmark Record** shall be a governed Evidence Product documenting a benchmark, test, comparison, performance result, model evaluation, infrastructure evaluation, network performance result, dashboard performance result, AI output evaluation, connector evaluation, interoperability result, security-adjacent result, or Core Build performance result used by Foundry.

**68.6.2 Benchmark Record Purpose.** Benchmark Records shall preserve benchmark scope, method, environment, workload, data, versions, provider dependencies, limitations, reproducibility status, public-safe status, and prohibited uses. They shall prevent benchmark results from becoming vendor rankings, procurement evidence, finance signals, maturity ratings, public authority approvals, or deployment evidence.

**68.6.3 Benchmark Record Elements.** Each Benchmark Record shall identify benchmark question, object tested, version, provider or component where relevant, environment, hardware, software, model, data, workload, method, metrics, expected result, actual result, comparator where applicable, configuration, reproducibility class, uncertainty, limitations, reviewer, conflicts, provider participation, public-safe status, correction pathway, archive rule, and prohibited interpretations.

**68.6.4 Benchmark Classes.** Benchmark Records may include performance benchmark, interoperability benchmark, AI evaluation benchmark, infrastructure benchmark, network benchmark, dashboard benchmark, simulation benchmark, secure-room benchmark, data-room benchmark, connector benchmark, Studio runtime benchmark, Core Build benchmark, and provider-neutrality benchmark.

**68.6.5 Comparative Benchmark Discipline.** Comparative Benchmark Records shall state configuration parity, workload relevance, provider participation, conflicts, statistical limitations where applicable, environmental limits, and public-safe restrictions. Comparative benchmarks shall not imply preferred vendor status unless a separate competent process expressly supports that exact meaning.

**68.6.6 Benchmark Publication.** Benchmark results may be public-safe summarized only where review confirms that public release will not create vendor ranking, procurement implication, finance implication, public authority implication, false maturity, or deployment overclaim. Provider names may be aggregated, masked, restricted, or omitted where appropriate.

**68.6.7 Benchmark Record Boundary.** Benchmark completion, high score, comparative result, benchmark pass, public-safe summary, Core Build performance, Studio performance, or Marketplace reference shall not create certification, provider validation, procurement status, financeability, insurability, public authority approval, maturity status, consent, deployment authorization, or execution authority.

**68.6.8 Benchmark Record Correction.** Benchmark Records shall be corrected where environment is misstated, versions change, workload is unrepresentative, method is flawed, limitations are hidden, provider configuration changes, public-safe wording overclaims, or benchmark results are used as vendor ranking or deployment evidence.

**68.6.9 Benchmark Record Formula.** Benchmark Records shall follow the formula: **record the question, method, environment, workload, result, and limits; control comparative meaning; correct stale results; never let benchmark performance become certification, preferred-vendor status, procurement, finance, consent, deployment, or execution.**

***

### 68.7 Compute-Use Record

**68.7.1 Compute-Use Record Identity.** A **Compute-Use Record** shall be a governed Evidence Product documenting the compute resources used for a Foundry activity, including development compute, test compute, AI compute, simulation compute, digital twin compute, Observatory compute, dashboard compute, Studio runtime compute, secure-room compute, data-room compute, Core Build compute, Nexus Universe compute, national compute, sovereign compute, edge compute, support compute, correction compute, archive compute, and teardown compute.

**68.7.2 Compute-Use Record Purpose.** Compute-Use Records shall make compute use traceable for reproducibility, cost or resource stewardship where relevant, resource allocation, provider-neutrality, sovereign requirements, AI review, energy and resilience considerations where relevant, support planning, teardown, and correction. Compute-use visibility shall not create approval or execution authority.

**68.7.3 Compute-Use Record Elements.** Each Compute-Use Record shall identify compute purpose, workload, object supported, compute class, provider or host, region or jurisdiction where relevant, hardware class, accelerator use where applicable, runtime duration, quota or allocation, data class, AI class, security class, sovereign or national requirements, support status, teardown status, reviewer where required, correction pathway, archive rule, and prohibited interpretations.

**68.7.4 Compute Classes.** Compute-use classes may include CPU, GPU, accelerator, HPC, sovereign compute, cloud compute, hybrid compute, edge compute, secure compute, confidential compute, compute-to-data, batch compute, interactive compute, inference compute, training or fine-tuning compute where permitted, simulation compute, dashboard compute, and archive compute.

**68.7.5 AI Compute Controls.** Compute-Use Records involving AI shall identify whether compute was used for inference, retrieval, embedding, evaluation, red-teaming, training, fine-tuning, agent workflow, or output generation. Training or fine-tuning shall not be inferred from general AI compute use.

**68.7.6 Scarce Compute Accountability.** Where scarce compute is used, the Compute-Use Record shall identify allocation basis, duration, priority reason, sponsor or provider relationship if any, and teardown status. Scarce compute allocation shall not imply object priority beyond record.

**68.7.7 Compute-Use Record Boundary.** Compute-use documentation, high-performance compute access, GPU allocation, sovereign compute use, Core Build compute use, successful run, or compute-use publication shall not create certification, public authority approval, procurement status, financeability, maturity status, consent, deployment authorization, operational command, or execution authority.

**68.7.8 Compute-Use Record Correction.** Compute-Use Records shall be corrected where provider, region, allocation, workload, AI use, data class, teardown status, or resource scarcity is misstated, or compute-use is treated as maturity, approval, or execution capacity.

**68.7.9 Compute-Use Record Formula.** Compute-Use Records shall follow the formula: **record compute purpose, environment, workload, sensitivity, allocation, and teardown; disclose scarce and provider-dependent compute; correct compute-use drift; never let compute use become approval, maturity, deployment, or execution.**

***

### 68.8 Network Performance Record

**68.8.1 Network Performance Record Identity.** A **Network Performance Record** shall be a governed Evidence Product documenting network performance, connectivity, latency, throughput, packet loss, route behavior, peering behavior, secure link behavior, public demonstration network behavior, Science DMZ or research data zone behavior where applicable, National Node exchange behavior, Observatory telemetry behavior, Studio runtime network behavior, Core Build network behavior, or degraded-mode network behavior.

**68.8.2 Network Performance Record Purpose.** Network Performance Records shall make network behavior traceable for testing, support, reliability, Core Build learning, Observatory learning, Studio runtime planning, National Node exchange planning, and handoff dependency mapping. They shall not become network certification, provider ranking, public authority approval, procurement evidence, finance signal, or deployment authorization.

**68.8.3 Network Performance Record Elements.** Each Network Performance Record shall identify network purpose, environment, route or zone class, endpoints, provider or host where relevant, test method, time period, bandwidth assumptions, latency, throughput, packet loss, failure modes, security controls, data classes traversed, monitoring status where appropriate, limitations, reviewer where required, correction pathway, archive rule, and prohibited interpretations.

**68.8.4 Network Performance Classes.** Records may include development network performance, test network performance, secure-room network performance, data-room network performance, Studio network performance, Observatory network performance, dashboard network performance, Marketplace network performance, Registry network performance, National Node exchange performance, Core Build performance, public demonstration performance, partner contribution performance, and degraded-mode performance.

**68.8.5 Sensitive Network Controls.** Network Performance Records shall not expose sensitive topology, cyber-sensitive endpoints, infrastructure-sensitive routes, public authority-sensitive connectivity, national-sensitive exchanges, or exploitable details beyond authorized audiences.

**68.8.6 Comparative Network Performance.** Comparative network performance involving providers, regions, networks, clouds, or hosts shall follow Benchmark Neutrality and shall not imply preferred provider, procurement ranking, or deployment suitability.

**68.8.7 Network Performance Record Boundary.** Network performance result, high-throughput result, low-latency result, successful peering, secure link, Core Build network success, or National Node exchange test shall not create network certification, provider validation, procurement status, financeability, public authority approval, maturity status, consent, deployment authorization, or execution authority.

**68.8.8 Network Performance Record Correction.** Records shall be corrected where endpoints change, routes change, provider conditions change, test environment is misstated, performance is generalized beyond scope, sensitive topology is exposed, or network performance is used as deployment evidence.

**68.8.9 Network Performance Record Formula.** Network Performance Records shall follow the formula: **record network behavior by environment and route; protect sensitive topology; state performance limits; correct stale results; never let network performance become certification, provider preference, procurement signal, or deployment authority.**

***

### 68.9 DRI Record

**68.9.1 DRI Record Identity.** A **DRI Record** shall be a governed Evidence Product documenting a Disaster Resilience Index, Disaster Risk Intelligence output, or equivalent DRI-related method, indicator, score, label, dashboard element, scenario input, Observatory linkage, National Portfolio input, public authority learning input, finance-readable dependency question, public-safe summary, or handoff dependency note used within Foundry.

**68.9.2 DRI Record Purpose.** DRI Records shall make disaster-risk and resilience-related outputs traceable, method-bounded, uncertainty-labeled, public-safe, safeguard-aware, nationally routed where required, and correctionable. A DRI Record shall support learning and dependency mapping; it shall not create public warning, official risk classification, insurance determination, investment signal, procurement priority, or public authority decision.

**68.9.3 DRI Record Elements.** Each DRI Record shall identify DRI purpose, geography where applicable, hazard classes, indicators, data sources, method, assumptions, weighting if any, uncertainty, confidence, limitations, public-safe class, sensitive geographies, community safeguard relevance, Indigenous protocol relevance where applicable, public authority relevance, finance-readability relevance, dashboard relationship, reviewer, correction pathway, archive rule, and prohibited interpretations.

**68.9.4 DRI Classes.** DRI Records may include indicator library records, hazard indicator records, resilience indicator records, exposure indicator records, vulnerability indicator records, capacity indicator records, public authority learning records, Observatory-linked DRI records, dashboard DRI records, scenario DRI records, national DRI records, and public-safe DRI summaries.

**68.9.5 DRI Public-Safe Controls.** DRI outputs shall be reviewed to avoid public warning implication, country ranking misuse, community stigmatization, sensitive location exposure, insurance signal, investment signal, public authority classification, financeability implication, procurement implication, consent implication, deployment implication, or false precision.

**68.9.6 DRI and Finance-Readable Use.** DRI Records may support finance-readable scenario questions or disaster risk finance simulation support only with no-reliance language and without underwriting, insurance approval, investment advice, public finance allocation, donor approval, or rating meaning.

**68.9.7 DRI Record Boundary.** DRI Record creation, DRI score, indicator, dashboard, public-safe summary, National Portfolio use, public authority learning use, or finance-readable mapping shall not create public warning, official classification, insurance determination, investment signal, procurement priority, public authority approval, financeability, consent, deployment authorization, or execution authority.

**68.9.8 DRI Record Correction.** DRI Records shall be corrected where indicators change, data becomes stale, weighting is wrong, uncertainty is hidden, public-safe language overclaims, sensitive places are exposed, or DRI outputs are used as warning, rating, insurance, investment, procurement, or deployment evidence.

**68.9.9 DRI Record Formula.** DRI Records shall follow the formula: **record disaster-risk indicators, methods, uncertainty, sensitivity, and limits; use DRI for learning and dependency questions; correct indicator drift; never let DRI become warning, rating, insurance, finance, procurement, consent, deployment, or execution.**

***

### 68.10 Observatory Record

**68.10.1 Observatory Record Identity.** An **Observatory Record** shall be a governed Evidence Product documenting an Observatory object, signal, sensor pathway, Edge input, telemetry stream, geospatial layer, Earth observation source, indicator, pipeline, dashboard, DRI linkage, GRIx context, digital twin input, confidence label, uncertainty label, drift label, public-safe observability output, national routing relationship, or archive element used within Nexus Foundry.

**68.10.2 Observatory Record Purpose.** Observatory Records shall make systems visibility traceable, classified, validated within scope, uncertainty-labeled, public-safe, safeguard-aware, nationally routed where required, and correctionable. They shall preserve the distinction between observation and warning, observation and surveillance, observation and command, and observation and public authority decision.

**68.10.3 Observatory Record Elements.** Each Observatory Record shall identify Observatory purpose, signal source, sensor or Edge source where applicable, geospatial layer, data class, sensitivity class, indicator definition, pipeline method, update cadence, validation status, confidence, uncertainty, drift, dashboard relationship, digital twin relationship, public-safe status, national routing, safeguard relevance, reviewer, correction pathway, archive rule, and prohibited interpretations.

**68.10.4 Observatory Classes.** Observatory Records may include signal records, sensor records, Edge records, telemetry records, geospatial records, Earth observation records, indicator records, pipeline records, DRI linkage records, GRIx context records, digital twin input records, dashboard records, public-safe observability records, and archive records.

**68.10.5 Sensitive Visibility Controls.** Observatory Records shall identify sensitive infrastructure, cyber-sensitive telemetry, sensitive geographies, vulnerable communities, protected knowledge, Indigenous-sensitive places or knowledge where applicable, public authority-sensitive signals, national-sensitive information, and publication restrictions.

**68.10.6 Drift and Confidence.** Observatory Records shall include confidence, uncertainty, freshness, and drift where relevant. Live or near-real-time signals shall not be treated as verified truth without validation. Missingness, sensor drift, latency, and data gaps shall be visible where reliance risk exists.

**68.10.7 Observatory Record Boundary.** Observatory Record creation, signal access, dashboard activation, DRI linkage, GRIx context, digital twin input, public-safe observability output, or National Portfolio use shall not create public warning, official risk classification, surveillance authority, insurance determination, investment signal, procurement priority, public authority approval, consent, deployment authorization, or operational command.

**68.10.8 Observatory Record Correction.** Observatory Records shall be corrected where signals drift, sensors fail, geospatial sensitivity is missed, uncertainty is hidden, public-safe labels fail, national routing is bypassed, or Observatory outputs are used as warning, surveillance, rating, or command.

**68.10.9 Observatory Record Formula.** Observatory Records shall follow the formula: **record signals, sources, indicators, confidence, uncertainty, drift, and sensitivity; separate observation from command; correct observability drift; never let Observatory evidence become warning, surveillance, finance, procurement, consent, deployment, or execution.**

***

### 68.11 Proof Record

**68.11.1 Proof Record Identity.** A **Proof Record** shall be a governed Evidence Product documenting that a defined action, review, test, build, release, correction, publication, support update, Registry update, Marketplace update, Studio action, teardown, data-room output review, secure-room output review, compute use, network test, dashboard label, AI output review, public-safe review, safeguard review, or handoff dependency action occurred under recorded conditions.

**68.11.2 Proof Record Purpose.** Proof Records shall provide traceable evidence that a specified procedural or technical fact occurred. They shall support validity-by-record, accountability, correctionability, auditability within scope, and institutional memory. A Proof Record shall not prove external approval, legal compliance, public authority approval, procurement suitability, financeability, consent, deployment authorization, or execution authority unless the proof is explicitly limited to a competent external record that itself creates such status.

**68.11.3 Proof Record Elements.** Each Proof Record shall identify proof purpose, action proved, object, version, actor or role, date and time where required, source records, method of proof, evidence artifact, environment, reviewer or witness where required, limitations, status created within Foundry if any, correction pathway, archive rule, and prohibited interpretations.

**68.11.4 Proof Record Classes.** Proof Records may include review proof, test proof, build proof, release proof, publication proof, support proof, correction proof, teardown proof, archive proof, data-room output proof, secure-room output proof, compute-use proof, network-test proof, AI-review proof, public-safe-review proof, safeguard-review proof, Registry-update proof, Marketplace-update proof, Studio-action proof, and handoff-dependency proof.

**68.11.5 Proof and Validity-by-Record.** Proof Records may create Foundry validity for the specific recorded action, status, or procedural fact within Foundry. They shall not create external validity unless tied to a competent external record and interpreted only within that external record’s scope.

**68.11.6 Proof Integrity.** Proof Records shall be tamper-resistant to the degree appropriate to risk, linked to source records, versioned, access-controlled where needed, corrected rather than silently overwritten, and archived where no longer current.

**68.11.7 Proof Record Boundary.** Proof Record creation, proof receipt, logged action, timestamp, signature, hash, verification, or Registry reference shall not create certification, legal compliance, public authority approval, procurement status, financeability, insurability, consent, deployment authorization, operational command, or execution authority by implication.

**68.11.8 Proof Record Correction.** Proof Records shall be corrected where action was misrecorded, evidence artifact is wrong, actor role is overstated, status created is misunderstood, timestamp is wrong, proof is incomplete, or Proof Record is used as approval beyond scope.

**68.11.9 Proof Record Formula.** Proof Records shall follow the formula: **prove only the recorded action under recorded conditions; preserve source and version; correct proof errors visibly; archive procedural memory; never let proof of process become proof of approval, consent, deployment, or execution.**

***

### 68.12 Public-Safe Evidence Summary

**68.12.1 Public-Safe Evidence Summary Identity.** A **Public-Safe Evidence Summary** shall be a governed Evidence Product that translates Evidence Packs, Method Notes, Dataset Records, Model Cards, System Cards, Benchmark Records, Compute-Use Records, Network Performance Records, DRI Records, Observatory Records, Proof Records, Simulation Records, or review findings into language suitable for a defined public, controlled-public, public authority learning, Marketplace, Registry, Studio, Academy, National Portfolio, Nexus Universe, media-facing, community-facing, or capital-reader-facing audience.

**68.12.2 Public-Safe Evidence Summary Purpose.** Public-Safe Evidence Summaries shall make evidence understandable without creating unsupported certainty, public warning, official classification, public authority approval, financeability, procurement status, provider validation, sponsor endorsement, community consent, Indigenous consent where applicable, deployment authorization, or execution authority.

**68.12.3 Summary Record.** Each Public-Safe Evidence Summary shall have a Summary Record identifying source Evidence Products, audience, channel, public-safe class, data sensitivity, public authority sensitivity, finance or procurement sensitivity, safeguard sensitivity, required labels, uncertainty statement, limitation statement, no-conversion language, accessibility status, translation status where applicable, reviewer, correction pathway, withdrawal rule, archive rule, and prohibited interpretations.

**68.12.4 Summary Content Requirements.** Public-Safe Evidence Summaries shall state what was reviewed, what the evidence supports, what remains uncertain, what cannot be inferred, what limitations apply, what support status applies, what correction pathway exists, and what claims are prohibited. They shall not simplify away essential boundaries.

**68.12.5 Audience-Specific Summaries.** A public-facing summary, public authority learning summary, capital-reader summary, community-facing summary, Indigenous-context summary where applicable, Marketplace description, Registry description, Studio explanation, and Academy summary may require different language, labels, access controls, and review. One summary shall not be reused across audiences without review.

**68.12.6 Visual Evidence Summaries.** Where summaries use charts, maps, dashboards, icons, rankings, thresholds, or score-like visuals, visual public-safe review shall apply. Visual design shall not create false precision, alarm, rating, procurement implication, finance implication, or public authority implication.

**68.12.7 Public-Safe Evidence Summary Boundary.** A Public-Safe Evidence Summary, plain-language summary, dashboard explanation, public report, Marketplace description, Registry description, Studio explanation, or capital-reader summary shall not create public warning, official classification, certification, procurement status, financeability, public authority approval, consent, deployment authorization, or execution authority.

**68.12.8 Public-Safe Evidence Summary Correction.** Summaries shall be corrected, restricted, withdrawn, superseded, or archived where source evidence changes, uncertainty is omitted, translation changes meaning, accessibility fails, visual design overclaims, finance or procurement wording overclaims, public authority meaning is overstated, or summary is used as approval.

**68.12.9 Public-Safe Evidence Summary Formula.** Public-Safe Evidence Summaries shall follow the formula: **translate evidence for a defined audience; preserve uncertainty, limits, and no-conversion language; review visuals and translations; correct public meaning; never let summary become warning, rating, approval, finance, procurement, consent, deployment, or execution.**

***

### 68.13 Evidence Product Review

**68.13.1 Evidence Product Review Identity.** **Evidence Product Review** shall be the governed review of Evidence Packs, Method Notes, Dataset Records, Model Cards, System Cards, Benchmark Records, Compute-Use Records, Network Performance Records, DRI Records, Observatory Records, Proof Records, Public-Safe Evidence Summaries, Simulation-to-Evidence Conversion Records, and related evidence outputs before they are released, listed, registered, Studio-used, public-safe-published, National-Portfolio-used, Core-Build-used, Nexus-Universe-used, readiness-mapped, support-classified, or handoff-adjacent.

**68.13.2 Review Purpose.** Evidence Product Review shall ensure that Evidence Products are source-grounded, method-bounded, uncertainty-labeled, limitation-aware, data-classified, AI-reviewed where applicable, cyber-aware where applicable, public-safe where applicable, safeguard-reviewed where applicable, national-routing-aware, support-aware, correctionable, and archive-ready.

**68.13.3 Review Record.** Each Evidence Product Review shall have a Review Record identifying Evidence Product, version, review scope, source records examined, evidence sufficiency, method sufficiency, data sufficiency, model sufficiency, system sufficiency, benchmark sufficiency, simulation sufficiency, proof sufficiency, public-safe status, safeguard status, national routing, reviewer, conflicts, accepted elements, rejected elements, required corrections, release limits, archive rule, and prohibited interpretations.

**68.13.4 Review Criteria.** Evidence Product Review shall assess traceability, source quality, currency, relevance, methodology, uncertainty, limitations, reproducibility where appropriate, data classification, AI involvement, model limitations, benchmark neutrality, public-safe language, safeguard sufficiency, national routing, support status, and downstream-use limits.

**68.13.5 Review Escalation.** Evidence Products involving sensitive data, AI systems, dual-use capability, cyber-sensitive materials, public authority-sensitive materials, finance-readable materials, procurement-sensitive materials, community-sensitive materials, Indigenous protocols where applicable, protected knowledge, public-facing claims, or handoff proximity shall be escalated to the applicable review pathways.

**68.13.6 Conditional Acceptance.** Evidence Products may be accepted with limitations only where limitations are recorded, visible to intended users, compatible with intended use, and linked to correction or renewal. Hidden limitations shall not justify public-safe release, Marketplace listing, Registry status, Studio use, or handoff adjacency.

**68.13.7 Evidence Product Review Boundary.** Evidence Product Review completion, positive review, acceptance-with-limitations, Evidence Pack approval within Foundry, Dataset Record acceptance, Model Card acceptance, System Card acceptance, Benchmark Record acceptance, Proof Record acceptance, or Public-Safe Evidence Summary release shall not create scientific consensus, certification, public authority approval, procurement status, financeability, insurability, maturity certification, consent, deployment authorization, or execution authority.

**68.13.8 Evidence Product Review Correction.** Review Records shall be corrected where review scope is incomplete, conflicts are omitted, sources are wrong, limitations are hidden, public-safe meaning fails, safeguards are incomplete, national routing is missed, or review status is used as approval.

**68.13.9 Evidence Product Review Formula.** Evidence Product Review shall follow the formula: **review evidence products by source, method, uncertainty, safeguards, and use limits; escalate sensitive cases; accept only within scope; correct review drift; never let evidence review become certification, approval, finance, procurement, consent, deployment, or execution.**

***

### 68.14 Evidence Product Correction

**68.14.1 Evidence Product Correction Identity.** **Evidence Product Correction** shall be the governed process for correcting, restricting, superseding, withdrawing, relabeling, republishing, recalling, retiring, or archiving Evidence Products that are wrong, stale, incomplete, misleading, unsafe, overclaimed, unsupported, misused, or no longer current.

**68.14.2 Correction Purpose.** Evidence Product Correction shall preserve evidence integrity, public-safe meaning, source truth, method discipline, uncertainty honesty, safeguard protection, national routing, support status, Marketplace accuracy, Registry truth, Studio safety, and handoff dependency integrity. Correction shall be treated as evidence quality, not reputational failure.

**68.14.3 Correction Record.** Each material Evidence Product Correction shall have a Correction Record identifying Evidence Product, version, correction trigger, prior statement or record, corrected statement or record, affected sources, affected methods, affected datasets, affected models, affected systems, affected benchmarks, affected proof records, affected public-safe summaries, affected dashboards, affected Marketplace listings, affected Registry records, affected Studio runtimes, affected National Portfolio materials, affected handoff materials, notice needs, recurrence controls, archive rule, and prohibited interpretations.

**68.14.4 Correction Triggers.** Correction may be triggered by source change, data correction, model drift, method flaw, benchmark flaw, simulation overclaim, proof error, public-safe misunderstanding, dashboard mislabeling, uncertainty omission, safeguard failure, protected knowledge exposure, Indigenous protocol concern where applicable, public authority overclaim, finance overclaim, procurement overclaim, consent overclaim, provider-neutrality incident, support status change, or archive misuse.

**68.14.5 Correction Actions.** Correction actions may include source update, method update, dataset reclassification, Model Card update, System Card update, Benchmark Record correction, Compute-Use Record correction, Network Performance Record correction, DRI correction, Observatory correction, Proof Record correction, Public-Safe Evidence Summary correction, Marketplace correction, Registry correction, Studio pause, dashboard withdrawal, public-safe notice, targeted notice, handoff recall, support reclassification, withdrawal, retirement, archive, sealing, or deletion where required.

**68.14.6 Public Repair.** Where Evidence Products have been publicly or widely shared and reliance risk exists, correction may require public-safe clarification, correction notice, withdrawal notice, supersession notice, updated Registry status, Marketplace update, Studio update, dashboard notice, or targeted notice to affected recipients.

**68.14.7 Evidence Product Correction Boundary.** Evidence Product Correction, correction notice, withdrawal, supersession, recall, Registry correction, Marketplace correction, Studio pause, or handoff recall shall not create legal finding, public authority finding, procurement finding, finance conclusion, consent determination, deployment denial, or execution effect beyond the Correction Record.

**68.14.8 Non-Retaliation.** Persons identifying evidence errors, source problems, method flaws, dataset issues, model drift, benchmark misuse, public-safe overclaim, safeguard concern, national routing issue, provider-neutrality concern, or archive misuse in good faith shall be protected. Correction reports shall be treated as public-good integrity inputs.

**68.14.9 Evidence Product Correction Formula.** Evidence Product Correction shall follow the formula: **detect evidence drift; contain misleading use; correct source, method, data, model, proof, and summary records; notify where reliance exists; archive prior states; never hide correction to preserve apparent authority.**

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### 68.15 Evidence Product Archive

**68.15.1 Evidence Product Archive Identity.** The **Evidence Product Archive** shall be the governed memory surface for non-current, superseded, withdrawn, corrected, restricted, retired, sealed, deletion-verified, or historically preserved Evidence Packs, Method Notes, Dataset Records, Model Cards, System Cards, Benchmark Records, Compute-Use Records, Network Performance Records, DRI Records, Observatory Records, Proof Records, Public-Safe Evidence Summaries, Evidence Product Reviews, Evidence Product Corrections, Simulation-to-Evidence Conversion Records, and related evidence outputs.

**68.15.2 Archive Purpose.** Evidence Product Archive shall preserve institutional memory without preserving current authority. It shall allow Foundry to understand what evidence existed, what sources were used, what methods were applied, what assumptions were made, what uncertainty was known, what limitations applied, what was corrected, what was withdrawn, what was public-safe-published, what was restricted, what was used downstream, and what future use is prohibited.

**68.15.3 Archive Record.** Each archived Evidence Product shall have an Archive Record identifying product, version, prior status, archive class, archive reason, active-use period, source records, method records, dataset records, model records, system records, benchmark records, proof records, public-safe release history, review history, correction history, Marketplace history, Registry history, Studio history, National Portfolio relationship, public authority learning relationship, finance-readability relationship, handoff relationship where applicable, sensitivity class, access restrictions, retention rule, deletion or sealing rule where applicable, reinstatement conditions, future-use restrictions, and prohibited interpretations.

**68.15.4 Archive Classes.** Evidence Product Archive classes may include public archive, controlled archive, restricted archive, secure archive, national archive, public authority learning archive, finance-readable archive, disaster-risk archive, Observatory archive, DRI archive, Studio archive, Core Build archive, Nexus Universe archive, National Portfolio archive, correction archive, support archive, sealed archive, deletion-verified archive, and non-continuation archive.

**68.15.5 Archive Access Discipline.** Access to archived Evidence Products shall be governed by privacy, data sensitivity, protected knowledge, Indigenous-sensitive knowledge where applicable, community sensitivity, geospatial sensitivity, cyber sensitivity, infrastructure sensitivity, health sensitivity, public authority sensitivity, provider confidentiality, sponsor confidentiality, finance-reader materials, procurement-sensitive materials, legal sensitivity, national routing, and public-safe rules. Archive existence shall not make archived materials public.

**68.15.6 Archive Without Current Status.** Archived Evidence Products shall not be cited as current evidence, current method, current dataset permission, current model validity, current benchmark result, current DRI output, current Observatory output, current Proof Record, current Public-Safe Evidence Summary, current Registry basis, current Marketplace basis, current Studio basis, current National Portfolio basis, current readiness basis, current handoff basis, public warning, approval, consent, deployment authorization, or execution authority unless reinstated by current review and record.

**68.15.7 Reinstatement.** Reinstatement of an archived Evidence Product shall require current review of source validity, method validity, dataset permission, model status, system status, benchmark status, proof validity, uncertainty, public-safe meaning, safeguard conditions, national routing, support status, Marketplace status, Registry status, Studio status, intended audience, and no-conversion language. Copying or citing an archived product shall not reinstate current status.

**68.15.8 Archive Correction.** Evidence Product Archive Records shall be corrected where archive class is wrong, sensitivity changes, retention rules change, deletion obligations arise, public display overclaims, archived materials are exposed improperly, Marketplace or Registry archive status is wrong, Studio runtime persists, or archived Evidence Products are cited as current authority.

**68.15.9 Final Evidence Products Formula.** The controlling Evidence Products Formula is that **Evidence Packs assemble source-grounded evidence without certification; Method Notes make methods repeatable without approval; Dataset Records document data without granting permission; Model Cards document models without AI certification; System Cards document systems without deployment authority; Benchmark Records preserve test meaning without provider ranking or procurement signal; Compute-Use Records record compute without maturity or execution overclaim; Network Performance Records record connectivity without provider validation; DRI Records support disaster-risk learning without warning, rating, or insurance determination; Observatory Records support visibility without surveillance, warning, or command; Proof Records prove specific recorded actions without proving external approval; Public-Safe Evidence Summaries communicate evidence without official status; Evidence Product Review controls use without certification; Evidence Product Correction repairs evidence truth without external legal or public authority effect; and Evidence Product Archive preserves institutional memory without current authority. No Evidence Pack, Method Note, Dataset Record, Model Card, System Card, Benchmark Record, Compute-Use Record, Network Performance Record, DRI Record, Observatory Record, Proof Record, Public-Safe Evidence Summary, Evidence Product Review, Evidence Product Correction, Evidence Product Archive, Registry reference, Marketplace reference, Studio use, National Portfolio use, Core Build use, Nexus Universe use, public authority learning use, finance-readable mapping, or handoff dependency package creates scientific consensus, recognition, certification, accreditation, public authority approval, procurement status, commercial approval, financeability, insurability, maturity certification, community consent, Indigenous consent where applicable, deployment authorization, operational command, or execution authority by implication.**

## 69. Proof, Provenance, and Verifiable Compute

### 69.1 Provenance Requirements

**69.1.1 Provenance Identity.** **Provenance Requirements** shall be the Foundry requirements governing the origin, custody, transformation, review, compute context, workflow path, AI involvement, human involvement, system involvement, publication path, Registry relationship, Marketplace relationship, Studio relationship, support relationship, correction relationship, and archive relationship of Foundry objects, records, outputs, and evidence products. Provenance shall make it possible to understand where an output came from, how it was produced, what records support it, what systems touched it, what assumptions shaped it, what reviews applied, what limits remain, and what downstream claims are prohibited.

**69.1.2 Provenance Purpose.** Provenance Requirements shall protect Nexus Foundry against untraceable outputs, unverifiable claims, hidden data dependencies, hidden AI involvement, provider-shaped evidence, sponsor-shaped narratives, unsupported public-safe materials, undocumented simulations, undocumented compute use, unexplained dashboards, unclear Registry states, misleading Marketplace listings, unsupported Studio runtimes, and handoff packages without traceable basis. Provenance shall make records accountable; it shall not make outputs externally certified by implication.

**69.1.3 Provenance Record.** Each material Foundry object or output shall have a **Provenance Record** identifying object, version, creator or originating role, source records, data sources, method sources, model sources, system sources, compute environment, workflow path, AI involvement where applicable, human review, transformations, dependencies, reviewer, release class, support status, public-safe status, Registry relationship, Marketplace relationship, Studio relationship, correction pathway, archive rule, and prohibited interpretations.

**69.1.4 Provenance Scope.** Provenance Requirements shall apply to Evidence Products, Method Notes, Dataset Records, Model Cards, System Cards, Benchmark Records, Compute-Use Records, Network Performance Records, DRI Records, Observatory Records, Proof Records, Public-Safe Evidence Summaries, dashboards, agents, connectors, Packs, Rails, Deployment Units, Studio Runtime Packages, Marketplace listings, Registry records, National Portfolio objects, Core Build outputs, Nexus Universe outputs, public authority learning materials, finance-readable materials, safeguard materials, and lawful handoff dependency packages.

**69.1.5 Provenance Completeness.** Provenance shall be sufficient for the intended purpose and risk class. High-risk, public-facing, public authority-sensitive, finance-sensitive, procurement-sensitive, data-sensitive, AI-sensitive, cyber-sensitive, community-sensitive, Indigenous-sensitive where applicable, dual-use, or handoff-adjacent outputs shall require stronger provenance than low-risk internal learning outputs.

**69.1.6 Provenance Chain.** Provenance shall preserve chain-of-record from source to output, including source identity, data classification, method, transformation, compute context, model or AI involvement, review, release, publication, support, correction, and archive. A break in provenance shall be recorded as a limitation, blocker, or correction issue.

**69.1.7 Provenance Boundary.** Provenance completeness, source traceability, compute traceability, workflow traceability, proof receipt, cryptographic attestation, reproducibility record, or archive trace shall not create certification, accreditation, audit opinion, legal compliance, public authority approval, procurement status, financeability, insurability, maturity certification, consent, deployment authorization, operational command, or execution authority.

**69.1.8 Provenance Correction.** Provenance Records shall be corrected where source identity is wrong, source lineage is missing, data custody is unclear, transformations are omitted, AI involvement is hidden, compute records are incomplete, workflow paths are wrong, review status is overstated, or provenance is used as proof of approval beyond scope.

**69.1.9 Provenance Formula.** Provenance Requirements shall follow the formula: **record origin, custody, transformation, compute, workflow, AI involvement, review, release, support, correction, and archive; strengthen provenance by risk; correct lineage gaps; never let provenance become certification, public authority approval, financeability, procurement status, consent, deployment, or execution.**

***

### 69.2 Source Records

**69.2.1 Source Record Identity.** **Source Records** shall be the foundational records from which Foundry outputs, Evidence Products, dashboards, simulations, models, Packs, Rails, Registry states, Marketplace listings, Studio runtimes, public-safe summaries, readiness mappings, safeguard materials, National Portfolio objects, Core Build outputs, Nexus Universe outputs, and lawful handoff dependency packages derive their factual, methodological, technical, data, or institutional basis.

**69.2.2 Source Record Purpose.** Source Records shall prevent Foundry from relying on memory, informal statements, undocumented assumptions, meeting impressions, marketing materials, unsupported AI outputs, untraceable datasets, screenshots without provenance, copied code without lineage, or provider assertions without classification. Source Records shall make claims reviewable and correctionable.

**69.2.3 Source Record Elements.** Each Source Record shall identify source title, source type, source origin, author or originating body where known, date or version where applicable, custody, access class, reliability notes, data classification where applicable, permission or use limits where applicable, public-safe status where applicable, method relevance, evidence relevance, limitations, downstream-use limits, correction pathway, archive rule, and prohibited interpretations.

**69.2.4 Source Record Classes.** Source Records may include documents, datasets, code repositories, issue records, pull requests, model records, system records, meeting records, workshop records, public authority learning records, community input records, Indigenous protocol records where applicable, sensor records, Observatory records, DRI records, simulation records, benchmark records, compute records, network records, proof records, review records, correction records, and archive records.

**69.2.5 Source Quality Classification.** Source Records shall be classified according to relevance, currency, provenance, method quality, reliability, completeness, uncertainty, sensitivity, public-safe usability, and downstream-use limits. Classification shall be for Foundry review and shall not become external rating or approval.

**69.2.6 Source Hierarchy.** Where multiple sources conflict, Foundry shall identify the conflict, classify source quality, state uncertainty, and avoid unsupported synthesis. Later sources shall not automatically supersede earlier sources unless the record supports supersession. Public statements shall not override controlled records where controlled records govern status.

**69.2.7 Source Record Boundary.** Source Record existence, source quality classification, source inclusion, source citation, or source hierarchy shall not create factual certainty, scientific consensus, legal sufficiency, public authority approval, procurement status, financeability, consent, deployment authorization, or execution authority.

**69.2.8 Source Record Correction.** Source Records shall be corrected where source metadata is wrong, source reliability changes, permissions change, source use exceeds scope, conflicting sources emerge, source sensitivity changes, or source inclusion is treated as approval.

**69.2.9 Source Record Formula.** Source Records shall follow the formula: **identify sources before claims; classify source quality and limits; preserve conflicting evidence where relevant; correct source drift; never let source inclusion become truth, approval, consent, deployment, or execution.**

***

### 69.3 Compute Records

**69.3.1 Compute Record Identity.** **Compute Records** shall document the compute environments, workloads, resources, configurations, providers, hosts, regions, jurisdictions, hardware, software, model runtimes, secure compute, sovereign compute, edge compute, Studio compute, Core Build compute, Observatory compute, simulation compute, AI compute, and teardown compute used to produce or support Foundry outputs.

**69.3.2 Compute Record Purpose.** Compute Records shall make technical production traceable, reproducible where appropriate, resource-accountable, provider-neutrality-aware, sovereignty-aware, security-aware, and correctionable. They shall help Foundry understand whether an output was produced in a suitable environment, with suitable controls, and within recorded limitations.

**69.3.3 Compute Record Elements.** Each Compute Record shall identify compute purpose, object supported, workload, environment, provider or host, region or jurisdiction where applicable, hardware class, accelerator class where applicable, runtime class, operating environment, container or image where applicable, dependency versions where applicable, resource allocation, data class, AI class, security class, sovereign or national requirements, logging or monitoring where appropriate, teardown status, reviewer where required, correction pathway, archive rule, and prohibited interpretations.

**69.3.4 Compute Sensitivity Classes.** Compute Records shall identify whether compute was public-safe, controlled, restricted, secure-room, data-room, no-download, compute-to-data, national-only, sovereign-sensitive, public authority-sensitive, community-sensitive, Indigenous-sensitive where applicable, health-sensitive, infrastructure-sensitive, cyber-sensitive, AI-sensitive, or archive-only.

**69.3.5 Verifiable Compute Linkage.** Where verifiable compute methods, secure logs, reproducible environments, signed artifacts, hashes, trusted execution environments, confidential computing, remote attestation, or cryptographic attestations are available and appropriate, Compute Records may link to such proof. Absence of such proof shall be stated where material.

**69.3.6 Compute Drift.** Compute Records shall support correction where compute environment changes, model runtime changes, provider service changes, dependencies update, sovereign requirements change, secure-room status changes, or outputs cannot be reproduced in the recorded environment.

**69.3.7 Compute Record Boundary.** Compute Record existence, high-performance compute use, sovereign compute use, secure compute use, verifiable compute proof, confidential computing use, or compute traceability shall not create certification, cybersecurity certification, legal compliance, public authority approval, procurement status, financeability, maturity certification, consent, deployment authorization, operational readiness, or execution authority.

**69.3.8 Compute Record Correction.** Compute Records shall be corrected where environment details are incomplete, provider or region is wrong, AI compute use is misstated, data sensitivity is misclassified, teardown is incomplete, verifiable compute claims are overstated, or compute records are used as maturity or approval claims.

**69.3.9 Compute Record Formula.** Compute Records shall follow the formula: **record where and how computation occurred; classify sensitivity and sovereignty; link verifiable compute where available; correct compute drift; never let compute traceability become certification, approval, deployment, or execution.**

***

### 69.4 Workflow Records

**69.4.1 Workflow Record Identity.** **Workflow Records** shall document the ordered sequence of steps, roles, tools, records, inputs, transformations, reviews, tests, approvals within Foundry scope, releases, corrections, support actions, Registry updates, Marketplace updates, Studio actions, public-safe publication actions, teardown actions, and archive actions through which Foundry work moves.

**69.4.2 Workflow Record Purpose.** Workflow Records shall make production pathways traceable and correctable. They shall prevent outputs from appearing without visible pathway, review, test, support status, correction pathway, or archive rule. Workflow Records shall preserve validity-by-record and prevent informal movement from becoming institutional status.

**69.4.3 Workflow Record Elements.** Each Workflow Record shall identify workflow name, object, version, triggering event, steps completed, steps skipped with reason if applicable, roles involved, tools used, source records, compute records, data records, AI involvement where applicable, review records, test records, release records, support records, Registry records, Marketplace records, Studio records, correction records, archive records, timestamps where required, limitations, correction pathway, and prohibited interpretations.

**69.4.4 Workflow Classes.** Workflow Records may include Intake workflows, Backlog workflows, Quest workflows, Bounty workflows, Build workflows, Review workflows, Release workflows, Registry workflows, Marketplace workflows, Studio workflows, Evidence workflows, Data Room workflows, Secure Room workflows, AI workflows, Publication workflows, Support workflows, Correction workflows, Handoff-dependency workflows, Teardown workflows, and Archive workflows.

**69.4.5 Workflow Integrity.** Workflow Records shall identify required gates and whether each gate was satisfied, deferred, restricted, not applicable by record, or blocked. A workflow shall not silently bypass required Data Review, Cyber Review, AI Review, Public-Safe Review, Safeguard Review, National Routing Review, Release Review, Support Review, or Archive Review.

**69.4.6 Workflow Automation.** Workflow steps may be automated where appropriate, but automated workflow execution shall not create substantive approval unless the automation is expressly authorized for that status by record and within scope. Human review shall remain required for authority-sensitive meaning.

**69.4.7 Workflow Record Boundary.** Workflow completion, successful automation, status transition, review gate passage, release workflow, Registry workflow, Marketplace workflow, Studio workflow, or handoff workflow shall not create certification, public authority approval, procurement status, financeability, consent, deployment authorization, operational command, or execution authority.

**69.4.8 Workflow Record Correction.** Workflow Records shall be corrected where steps are missing, gates are bypassed, automation exceeds scope, timestamps are wrong, reviewer roles are overstated, required records are absent, or workflow completion is used as approval beyond scope.

**69.4.9 Workflow Record Formula.** Workflow Records shall follow the formula: **record the path from input to output; show gates, roles, tools, and records; prevent silent bypass; correct workflow drift; never let workflow completion become certification, consent, deployment, or execution.**

***

### 69.5 AI Workflow Records

**69.5.1 AI Workflow Record Identity.** **AI Workflow Records** shall document the role of AI models, AI systems, agents, retrieval systems, embedding stores, prompt workflows, tool calls, human review, output review, automated claim-prevention, red-team results, and correction actions in Foundry workflows.

**69.5.2 AI Workflow Record Purpose.** AI Workflow Records shall prevent hidden AI involvement, untraceable AI outputs, unauthorized data use, unsafe retrieval, prompt injection, tool overreach, hallucinated authority, unsupported summaries, public authority overclaim, finance or procurement overclaim, consent inference, deployment implication, and execution by agentic workflow.

**69.5.3 AI Workflow Record Elements.** Each AI Workflow Record shall identify AI workflow name, purpose, model or system, provider where applicable, version or versioning rule, data inputs, retrieval sources, embedding use, memory rule, prompt or workflow class where appropriate, tool permissions, agent autonomy level, human approval points, output class, review status, public-safe status, safeguard status, red-team status where applicable, shutdown triggers, correction pathway, archive rule, and prohibited interpretations.

**69.5.4 AI Involvement Classes.** AI involvement may be recorded as drafting support, summarization support, translation support, classification support, extraction support, analysis support, code support, dashboard support, evidence-support, review-support, publication-support, Studio runtime, agentic workflow, restricted AI workflow, no-AI workflow, or prohibited AI workflow.

**69.5.5 AI Output Lineage.** AI Workflow Records shall identify whether outputs are AI-generated, AI-assisted, human-reviewed, source-checked, public-safe reviewed, restricted, rejected, corrected, or released. AI outputs shall not be treated as source records unless the AI output itself is the object being reviewed.

**69.5.6 Authority-Sensitive AI Controls.** AI workflows involving public authority materials, finance-readable materials, procurement-sensitive materials, community-sensitive materials, Indigenous-sensitive materials where applicable, protected knowledge, public-safe publication, Registry status, Marketplace listing, Studio runtime, or handoff packages shall require human review and recorded limits.

**69.5.7 AI Workflow Record Boundary.** AI Workflow Record completion, AI traceability, model card, system card, human review, red-team pass, automated claim-prevention pass, or Studio AI workflow shall not certify AI safety, authorize sensitive data use, create public authority approval, procurement status, financeability, consent, deployment authorization, operational command, or execution authority.

**69.5.8 AI Workflow Record Correction.** AI Workflow Records shall be corrected where model versions change, retrieval sources change, tool permissions expand, AI involvement is hidden, outputs overclaim, memory rules fail, data use exceeds scope, or AI workflow records are used as AI certification.

**69.5.9 AI Workflow Record Formula.** AI Workflow Records shall follow the formula: **record AI involvement, data, tools, prompts or workflow class, human review, and output status; restrict authority-sensitive AI; correct AI drift; never let AI traceability become AI approval, consent, deployment, or execution.**

***

### 69.6 Proof Receipts Where Authorized

**69.6.1 Proof Receipt Identity.** **Proof Receipts** shall be bounded, governed, record-bearing receipts issued only where authorized to confirm that a specific Foundry action, status transition, review, test, release, correction, publication, Registry update, Marketplace update, Studio action, data-room output review, secure-room output review, support update, teardown, archive, or handoff-dependency action occurred under recorded conditions.

**69.6.2 Proof Receipt Purpose.** Proof Receipts shall provide traceable evidence of occurrence, sequence, status, or procedural completion within Foundry scope. They shall strengthen validity-by-record and correctionability. A Proof Receipt shall prove only the recorded procedural fact; it shall not certify the substantive merit or external legal effect of the underlying object unless the receipt expressly references a competent external record and remains limited to that record.

**69.6.3 Proof Receipt Record.** Each Proof Receipt shall identify receipt identifier, issuing function, authorized basis, action proved, object, version, actor or role, date and time where required, source records, method of proof, evidence artifact, status created within Foundry if any, limitations, verification method where applicable, correction pathway, archive rule, and prohibited interpretations.

**69.6.4 Authorized Receipt Classes.** Proof Receipts may be issued for Intake receipt, Build receipt, Review receipt, Test receipt, Release receipt, Public-Safe Review receipt, Registry Update receipt, Marketplace Update receipt, Studio Action receipt, Support Update receipt, Correction receipt, Data Room Output Review receipt, Secure Room Output Review receipt, Compute Use receipt, Teardown receipt, Archive receipt, and Handoff Dependency receipt, only where authorized by Foundry procedure.

**69.6.5 Receipt Issuance Controls.** Proof Receipts shall not be issued informally. Receipt issuance shall require authority by role, defined receipt class, source record, version reference, status statement, limitation statement, correction pathway, and archive pathway. Unauthorized receipt issuance shall be a boundary incident.

**69.6.6 Receipt Display and Use.** Proof Receipts may be displayed in Registry records, support records, release notes, controlled dashboards, handoff dependency packages, public-safe summaries, or archive records where appropriate. Display shall include no-conversion language appropriate to audience and risk.

**69.6.7 Proof Receipt Boundary.** Proof Receipt issuance, receipt identifier, timestamp, signature, hash, Registry link, Marketplace link, Studio link, handoff dependency link, or public-safe display shall not create certification, accreditation, legal compliance, public authority approval, procurement status, financeability, insurability, maturity certification, consent, deployment authorization, operational command, or execution authority.

**69.6.8 Proof Receipt Correction.** Proof Receipts shall be corrected, superseded, withdrawn, restricted, or archived where issued in error, source records are wrong, actor role is overstated, status is misunderstood, receipt scope is overclaimed, or receipt is used as approval beyond scope.

**69.6.9 Proof Receipt Formula.** Proof Receipts shall follow the formula: **issue only when authorized; prove only the recorded procedural fact; include limits and correction path; withdraw erroneous receipts; never let proof receipt become certification, approval, consent, deployment, or execution.**

***

### 69.7 Cryptographic Attestation Where Available

**69.7.1 Cryptographic Attestation Identity.** **Cryptographic Attestation Where Available** shall refer to the use of hashes, signatures, signed logs, secure timestamps, attestations, transparency logs, trusted execution evidence, remote attestation, confidential-computing attestations, verifiable build artifacts, signed releases, signed containers, signed datasets, signed model artifacts, signed workflow records, signed proof receipts, or equivalent mechanisms to support integrity, traceability, tamper-evidence, reproducibility, and verification within Foundry scope.

**69.7.2 Attestation Purpose.** Cryptographic attestation shall strengthen confidence that a record, artifact, dataset, model, container, release, workflow, proof receipt, compute event, or archive object has not been silently altered and can be linked to a recorded source, version, environment, actor, or process. It shall support trustworthiness; it shall not create substantive certification or external approval.

**69.7.3 Attestation Record.** Each material attestation shall have an Attestation Record identifying artifact or record attested, attestation method, signing role or system, key or trust mechanism, timestamp where applicable, hash or signature reference, verification method, scope, limitations, dependency on external services where applicable, retention rule, correction pathway, archive rule, and prohibited interpretations.

**69.7.4 Attestation Classes.** Attestation classes may include source-code attestation, build attestation, container attestation, dataset attestation, model attestation, workflow attestation, compute attestation, confidential-computing attestation, proof receipt attestation, release attestation, Registry attestation, Marketplace attestation, Studio package attestation, public-safe publication attestation, teardown attestation, and archive attestation.

**69.7.5 Key and Trust Controls.** Cryptographic attestation shall be governed by key management, signing authority, rotation, revocation, verification, access control, loss procedures, compromise procedures, and archive procedures proportionate to risk. A compromised or uncertain key shall trigger correction and potential withdrawal of affected attestations.

**69.7.6 Attestation Limits.** Attestation proves integrity or occurrence within its recorded scope; it does not prove truth, quality, safety, legality, public-safe meaning, public authority approval, financeability, procurement suitability, consent, deployment readiness, or execution authorization. A signed false record remains false and must be corrected.

**69.7.7 Cryptographic Attestation Boundary.** Cryptographic attestation, signed artifact, hash, timestamp, trusted execution evidence, remote attestation, signed release, or verification pass shall not create certification, cybersecurity certification, legal compliance, public authority approval, procurement status, financeability, insurability, maturity certification, consent, deployment authorization, operational readiness, or execution authority.

**69.7.8 Attestation Correction.** Attestation Records shall be corrected where signatures are invalid, keys are compromised, artifacts are mislabeled, hashes do not match, trust assumptions change, attestation scope is overstated, or cryptographic proof is used as substantive approval.

**69.7.9 Cryptographic Attestation Formula.** Cryptographic Attestation shall follow the formula: **attest integrity and occurrence where available; govern keys and verification; state scope and limits; correct compromised or false attestations; never let cryptographic proof become truth, certification, approval, consent, deployment, or execution.**

***

### 69.8 Reproducibility Records

**69.8.1 Reproducibility Record Identity.** **Reproducibility Records** shall document whether and how a Foundry output, test, build, analysis, evidence product, dashboard, simulation, AI evaluation, connector result, benchmark result, data transformation, compute result, network performance result, Studio runtime result, public-safe summary, or proof record can be reproduced, traced, re-run, verified, or only partially reproduced under recorded conditions.

**69.8.2 Reproducibility Purpose.** Reproducibility Records shall preserve checkability, accountability, and correctionability. They shall prevent Foundry outputs from depending on undocumented environments, untracked data, hidden prompts, changing model versions, unavailable APIs, unsupported services, manual transformations, private notebooks, or unrecorded provider conditions.

**69.8.3 Reproducibility Record Elements.** Each Reproducibility Record shall identify object, version, reproducibility class, source records, data inputs, data versions, code versions, model versions, system versions, environment, compute records, workflow records, dependencies, configuration, random seeds where applicable, tool versions, expected outputs, known variability, limitations, reviewer, correction pathway, archive rule, and prohibited interpretations.

**69.8.4 Reproducibility Classes.** Reproducibility classes may include fully reproducible, partially reproducible, traceable-only, method-reproducible, data-restricted, secure-room-only, compute-to-data-only, national-only, synthetic-data-only, model-version-dependent, provider-dependent, non-deterministic, non-reproducible-by-design due to rights or sensitivity, archived, or not reproducible.

**69.8.5 Sensitive Reproducibility.** Reproducibility shall not override data restrictions, privacy, protected knowledge, Indigenous protocols where applicable, secure-room rules, national routing, public authority sensitivity, cyber sensitivity, infrastructure sensitivity, provider confidentiality, or legal restrictions. Where full reproduction is unsafe or unlawful, Foundry may use controlled proof, synthetic data, aggregated reproduction, secure-room reproduction, or compute-to-data reproduction.

**69.8.6 AI Reproducibility.** AI reproducibility shall identify model version, system configuration, retrieval sources, tool permissions, prompt or workflow class where appropriate, memory settings, randomness settings where relevant, human review, output variability, and drift risk. AI output reproducibility shall not be overclaimed where nondeterminism or model changes affect results.

**69.8.7 Reproducibility Boundary.** Reproducibility status, successful rerun, traceability, deterministic output, reproducible benchmark, reproducible simulation, or reproducibility record shall not create scientific consensus, certification, public authority approval, procurement status, financeability, insurability, maturity certification, consent, deployment authorization, operational readiness, or execution authority.

**69.8.8 Reproducibility Correction.** Reproducibility Records shall be corrected where dependencies are missing, environments cannot be recreated, data versions are wrong, model versions change, outputs differ materially, sensitive restrictions were ignored, or reproducibility is used as approval.

**69.8.9 Reproducibility Record Formula.** Reproducibility Records shall follow the formula: **record inputs, code, models, environment, workflow, dependencies, and variability; classify reproducibility honestly; protect sensitive restrictions; correct irreproducible claims; never let reproducibility become universal validation, approval, consent, deployment, or execution.**

***

### 69.9 Limitations and Uncertainty

**69.9.1 Limitations and Uncertainty Identity.** **Limitations and Uncertainty** shall be mandatory elements of Foundry proof, provenance, verifiable compute, evidence, simulation, dashboard, AI workflow, benchmark, public-safe summary, Registry record, Marketplace listing, Studio runtime, National Portfolio material, public authority learning material, finance-readable material, and lawful handoff dependency package wherever reliance risk exists.

**69.9.2 Purpose.** Limitations and Uncertainty statements shall make visible what Foundry does not know, what it has not tested, what it cannot prove, what assumptions control the output, what data is incomplete, what methods are bounded, what model behavior is uncertain, what compute context limits reproducibility, what public-safe meaning is restricted, what support is limited, and what downstream claims are prohibited.

**69.9.3 Limitations and Uncertainty Record.** Each material statement shall identify object, version, limitation class, uncertainty source, affected claims, affected audience, data limitations, method limitations, model limitations, compute limitations, workflow limitations, reproducibility limitations, public-safe limitations, safeguard limitations, national routing limitations, support limitations, correction pathway, archive rule, and prohibited interpretations.

**69.9.4 Limitation Classes.** Limitation classes may include source limitation, data limitation, method limitation, model limitation, simulation limitation, benchmark limitation, compute limitation, network limitation, workflow limitation, AI limitation, security limitation, public-safe limitation, safeguard limitation, national-context limitation, translation limitation, accessibility limitation, support limitation, reproducibility limitation, and archive limitation.

**69.9.5 Uncertainty Display.** Where outputs are public-facing, dashboard-based, Studio-based, public authority-facing, capital-reader-facing, community-facing, National Portfolio-facing, or Marketplace-facing, uncertainty and limitations shall be visible to the intended audience. Hidden limitations shall not justify broad release.

**69.9.6 Uncertainty and Restriction.** Where limitations or uncertainty are too material to be safely communicated to the intended audience, the object shall be restricted, revised, withheld, withdrawn, or archived rather than released with insufficient disclaimers.

**69.9.7 Limitations Boundary.** Stating limitations shall not cure an otherwise unsafe, unauthorized, unsupported, or overclaimed output. A limitation statement shall not create permission to publish, deploy, finance, procure, approve, consent, execute, or rely beyond the record.

**69.9.8 Limitations Correction.** Limitations and Uncertainty Records shall be corrected where assumptions change, data changes, methods change, model behavior changes, uncertainty increases, support changes, public-safe interpretation changes, or limitations are used as liability shields for overclaim.

**69.9.9 Limitations and Uncertainty Formula.** Limitations and Uncertainty shall follow the formula: **state what is known, unknown, assumed, untested, unsupported, non-transferable, and prohibited; make limits visible; restrict outputs where limits cannot be safely communicated; never let limitation language become permission to overclaim.**

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### 69.10 Proof Without Certification Overclaim

**69.10.1 No Certification Overclaim Rule.** **Proof Without Certification Overclaim** shall be the controlling rule that no Provenance Record, Source Record, Compute Record, Workflow Record, AI Workflow Record, Proof Receipt, Cryptographic Attestation, Reproducibility Record, limitation statement, evidence record, test record, review record, Registry record, Marketplace listing, Studio runtime, public-safe summary, National Portfolio material, Core Build output, Nexus Universe output, or handoff dependency package shall be described or interpreted as certification, accreditation, approval, compliance determination, public authority decision, procurement qualification, financeability determination, insurance determination, maturity certification, consent, deployment authorization, operational command, or execution authority unless separately and lawfully created by competent actors and recorded as such.

**69.10.2 Purpose.** This rule shall preserve the difference between proof of occurrence, proof of provenance, proof of compute, proof of workflow, proof of review, proof of integrity, proof of reproducibility, proof of publication, proof of support, proof of correction, and proof of external approval. Foundry may prove that something happened; it shall not imply that what happened is externally approved.

**69.10.3 Required Boundary Language.** Proof materials shall include appropriate boundary language stating what the proof establishes and what it does not establish. Where audience risk is high, proof displays shall state no certification, no accreditation, no legal compliance determination, no public authority approval, no procurement effect, no finance or insurance effect, no consent effect, no deployment authorization, and no execution authority.

**69.10.4 Proof Scope Discipline.** Proof shall be scoped to the specific recorded action, artifact, environment, version, time, actor, workflow, or review. Proof of one step shall not prove the entire system. Proof of compute shall not prove truth. Proof of review shall not prove external approval. Proof of publication shall not prove official status. Proof of reproducibility shall not prove universal validity.

**69.10.5 External Record Distinction.** Where a competent external authority, public authority, certification body, court, regulator, procurement body, insurer, lender, donor, public finance actor, community authority, Indigenous authority where applicable, or implementation actor creates an external status, Foundry may reference that status only by exact record, scope, issuer, and limitation. Foundry shall not enlarge external status.

**69.10.6 Visual and Digital Display Controls.** Proof badges, receipts, hashes, signatures, Registry icons, Marketplace labels, Studio labels, dashboard labels, and public-safe graphics shall be designed to avoid certification-like, approval-like, rating-like, procurement-like, finance-like, consent-like, deployment-like, or execution-like interpretation.

**69.10.7 Proof Boundary.** Proof presence, proof completeness, attestation, receipt, signature, verification, reproducibility, or source traceability shall not create certification, accreditation, public authority approval, procurement status, financeability, insurability, maturity certification, consent, deployment authorization, operational readiness, or execution authority.

**69.10.8 Proof Overclaim Correction.** Proof displays, records, receipts, public materials, Registry records, Marketplace labels, Studio labels, and handoff materials shall be corrected where proof is read or used as certification, approval, procurement, finance, consent, deployment, or execution status.

**69.10.9 Proof Without Certification Formula.** Proof Without Certification Overclaim shall follow the formula: **prove occurrence and provenance within scope; state what proof does not prove; separate external approvals from Foundry proof; correct certification-like displays; never let proof become certification, authority, consent, deployment, or execution.**

***

### 69.11 Proof Misuse and Correction

**69.11.1 Proof Misuse Identity.** **Proof Misuse** shall be any actual, potential, perceived, or alleged use of Foundry proof, provenance, verifiable compute, source records, compute records, workflow records, AI workflow records, proof receipts, attestations, reproducibility records, test records, review records, Registry records, Marketplace labels, Studio labels, public-safe summaries, or handoff dependency records to imply status beyond their recorded scope.

**69.11.2 Misuse Purpose.** Proof Misuse discipline shall detect and repair overclaim before proof becomes false authority. It shall preserve validity-by-record, public-good integrity, public authority boundaries, finance boundaries, procurement neutrality, consent boundaries, provider neutrality, national ownership, support honesty, and correctionability.

**69.11.3 Misuse Classes.** Proof Misuse may include certification overclaim, compliance overclaim, public authority approval overclaim, procurement overclaim, financeability overclaim, insurability overclaim, maturity overclaim, provider validation overclaim, sponsor endorsement overclaim, consent overclaim, deployment authorization overclaim, operational readiness overclaim, execution authority overclaim, source certainty overclaim, compute truth overclaim, cryptographic proof overclaim, reproducibility overclaim, and archive-current-status overclaim.

**69.11.4 Misuse Record.** Each material Proof Misuse incident shall have a Misuse Record identifying proof object, misuse class, actor or surface involved where appropriate, affected records, affected public materials, affected Registry records, affected Marketplace listings, affected Studio runtimes, affected National Portfolio materials, affected public authority learning materials, affected finance-readable materials, affected handoff packages, containment action, correction pathway, notice requirement, archive rule, and prohibited interpretations.

**69.11.5 Containment Actions.** Containment may include changing wording, removing badges, restricting proof display, withdrawing proof receipt, correcting Registry status, correcting Marketplace listing, pausing Studio runtime, issuing public-safe clarification, notifying provider or sponsor, notifying recipients, recalling handoff materials, revising visual labels, restricting access, or archiving the misused proof.

**69.11.6 Correction Actions.** Correction shall restore exact proof meaning, including what occurred, what did not occur, what status was created within Foundry, what status was not created externally, what limitations apply, and what downstream uses are prohibited. Correction shall reach the surfaces where misuse occurred.

**69.11.7 Misuse Boundary.** Recording or correcting Proof Misuse shall not itself create legal finding, public authority finding, procurement finding, finance conclusion, insurance conclusion, consent determination, deployment decision, or execution effect beyond the correction record unless separately determined by competent authority.

**69.11.8 Non-Retaliation.** Persons identifying Proof Misuse in good faith shall be protected. Reports of proof overclaim, false proof display, receipt misuse, attestation misuse, Registry overclaim, Marketplace overclaim, Studio overclaim, or handoff overclaim shall be treated as public-good integrity inputs.

**69.11.9 Proof Misuse and Correction Formula.** Proof Misuse and Correction shall follow the formula: **detect proof overclaim; contain misleading displays; correct affected records and communications; notify where reliance exists; preserve learning; never allow proof misuse to become institutional truth.**

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### 69.12 Proof Archive

**69.12.1 Proof Archive Identity.** The **Proof Archive** shall be the governed memory surface for non-current, superseded, withdrawn, corrected, restricted, retired, sealed, deletion-verified, or historically preserved Provenance Records, Source Records, Compute Records, Workflow Records, AI Workflow Records, Proof Receipts, Cryptographic Attestation Records, Reproducibility Records, limitation statements, proof-misuse records, proof-correction records, proof displays, proof dashboards, Registry proof links, Marketplace proof links, Studio proof links, and handoff proof records.

**69.12.2 Archive Purpose.** The Proof Archive shall preserve institutional memory without preserving current proof status or external authority. It shall allow Foundry to understand what was proven, when it was proven, by whom or by what system, under what conditions, with what evidence, with what limitations, what was corrected, what was withdrawn, what was superseded, what was misused, and what future use is restricted.

**69.12.3 Proof Archive Record.** Each archived proof item shall have an Archive Record identifying proof item, version, prior status, archive class, archive reason, active-use period, source records, compute records, workflow records, AI workflow records where applicable, attestation records where applicable, reproducibility records, correction history, misuse history, public display history, Registry history, Marketplace history, Studio history, National Portfolio relationship, public authority learning relationship, finance-readable relationship, handoff relationship where applicable, sensitivity class, access restrictions, retention rule, deletion or sealing rule where applicable, reinstatement conditions, future-use restrictions, and prohibited interpretations.

**69.12.4 Archive Classes.** Proof Archive classes may include public archive, controlled archive, restricted archive, secure archive, national archive, public authority learning archive, finance-readable archive, Registry archive, Marketplace archive, Studio archive, Core Build archive, Nexus Universe archive, National Portfolio archive, correction archive, misuse archive, sealed archive, deletion-verified archive, and non-continuation archive.

**69.12.5 Archive Access Discipline.** Access to archived proof shall be governed by privacy, data sensitivity, cyber sensitivity, infrastructure sensitivity, protected knowledge, Indigenous-sensitive knowledge where applicable, community sensitivity, public authority sensitivity, provider confidentiality, sponsor confidentiality, finance-reader confidentiality, procurement sensitivity, legal sensitivity, national routing, and public-safe rules. Archive existence shall not make proof public.

**69.12.6 Archive Without Current Proof Status.** Archived proof shall not be cited as current proof, current provenance, current compute verification, current workflow status, current proof receipt, current attestation, current reproducibility status, current Registry status, current Marketplace status, current Studio status, current National Portfolio basis, current readiness basis, current handoff basis, public authority approval, consent, deployment authorization, or execution authority unless reinstated by current review and record.

**69.12.7 Reinstatement.** Reinstatement of archived proof shall require current review of source validity, compute validity, workflow validity, AI workflow status, attestation validity, reproducibility status, sensitivity, public-safe meaning, support status, Registry status, Marketplace status, Studio status, intended audience, and no-conversion language. Relinking an old hash, copying an old receipt, reopening a record, or citing an old proof shall not reinstate current status.

**69.12.8 Archive Correction.** Proof Archive Records shall be corrected where archive class is wrong, sensitivity changes, retention rules change, deletion obligations arise, proof is exposed improperly, archived proof is displayed as current, Registry or Marketplace archive status is wrong, Studio proof links persist, or archived proof is used as approval.

**69.12.9 Final Proof, Provenance, and Verifiable Compute Formula.** The controlling Proof, Provenance, and Verifiable Compute Formula is that **Provenance Requirements trace origin, custody, transformation, compute, workflow, AI involvement, review, release, support, correction, and archive; Source Records ground claims without becoming truth by themselves; Compute Records document where and how computation occurred without maturity or approval overclaim; Workflow Records show procedural movement without external status; AI Workflow Records expose AI involvement without AI certification; Proof Receipts prove only authorized procedural facts; Cryptographic Attestation supports integrity without proving truth or approval; Reproducibility Records make outputs checkable without universal validation; Limitations and Uncertainty make boundaries visible without licensing overclaim; Proof Without Certification Overclaim prevents proof from becoming external authority; Proof Misuse and Correction repairs overclaim; and Proof Archive preserves proof memory without current status. No provenance record, source record, compute record, workflow record, AI workflow record, proof receipt, cryptographic attestation, reproducibility record, limitation statement, proof display, proof dashboard, Registry proof link, Marketplace proof link, Studio proof link, public-safe summary, correction record, misuse record, archive record, National Portfolio use, Core Build use, Nexus Universe use, public authority learning use, finance-readable use, or handoff dependency package creates scientific consensus, recognition, certification, accreditation, audit opinion, legal compliance, public authority approval, procurement status, commercial approval, financeability, insurability, maturity certification, community consent, Indigenous consent where applicable, deployment authorization, operational command, or execution authority by implication.**


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