> For the complete documentation index, see [llms.txt](https://docs.therisk.global/organization/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.therisk.global/organization/cooperation/consortiums/frontiers/gra/membership/services/registry.md).

# Registry

{% hint style="warning" %}
**Historical layer.** This page belongs to the 2024–25 frontier layer. It is kept as written for the record, read with the current model. The [Nexus Standards](/organization/institutions/nexus-standards.md) named here does not exist. The current structure is in [Institutions](/organization/institutions.md) and [Governance in operation](/organization/governance-in-operation.md).
{% endhint %}

**Where this fits:** all six sectors ([The Model](/organization/model.md)) · [Labs](/organization/programme/labs.md), [Risk Academy](/organization/programme/academy.md) · earlier frontier layers of GCRI, GRF and GRA ([Institutions](/organization/institutions.md)) · historical layer (2024-25).

**In brief.** The AI Model Registry and Simulation Cloud Access module is a core element of the Nexus-as-a-Service (NXSaaS) architecture. It provides GRA members with secure, auditable, and programmable access to a global library of disaster risk reduction (DRR), climate resilience, and systems forecasting models, while enabling real-time simulation and anticipatory analysis across sovereign, regional, and institutional contexts. Read against the international frameworks it serves ([UN General Assembly 2015](https://www.undrr.org/publication/sendai-framework-disaster-risk-reduction-2015-2030); [United Nations 2021](https://www.un.org/en/common-agenda); [UN General Assembly 2024](https://undocs.org/A/RES/79/1)) and the Nexus Standards that govern its records ([NS-0](https://nexustandards.com/standards/ns-0/)). Frontier texts describe earlier designs: none records a treaty, legal personality, immunity, regulator status, issued credential or adopted instrument, and no institution holds supranational authority.

{% hint style="info" %}
**Read with the current model (2026-10-21).**

* Everything this page describes is a design in formation. No national, regional or global consortium is recorded as constituted or active; the current service level is R0, information and enquiries ([Status and service levels](/organization/governance-in-operation/status-and-service-levels.md)). Where the text below reads as operation, read it as design.
* Ordinary participation has no fee; selection precedes payment, and a seat never buys office, a technical conclusion, public authority or procurement treatment. Paid work, internships and fellowships are separate arrangements ([NLC](/organization/governance-in-operation/nlc.md); [NWG](/organization/governance-in-operation/nwg.md)).
* Recognition, scoring and validation record what was shown under stated conditions. None is a certification, licence, rating or approval, and no country or institution is ranked.
* There is no Nexus Standards. Nexus Standards is governed by the Global Standards Council, with GCRI Canada as secretariat and publisher of record; [NXS-NSF](/organization/systems/nxs-nsf.md) is the system for trust, authorization, mandate, policy and assurance.
  {% endhint %}

### **4.3 AI Model Registry and Simulation Cloud Access**

#### **4.3.1 Overview**

The **AI Model Registry and Simulation Cloud Access** module is a core element of the Nexus-as-a-Service (NXSaaS) architecture. It provides GRA members with secure, auditable, and programmable access to a global library of disaster risk reduction (DRR), climate resilience, and systems forecasting models, while enabling real-time simulation and anticipatory analysis across sovereign, regional, and institutional contexts.

This infrastructure not only democratizes access to frontier models but also ensures ethical deployment, regional customization, explainability, and adaptive refinement based on evolving hazards and development priorities. The AI/ML components of the Nexus Ecosystem are not generic—each is designed, trained, audited, and governed for **public-good use**, **policy support**, and **cross-sector risk reduction** in alignment with the SDGs, Sendai Framework, Paris Agreement, and the Pact for the Future.

***

#### **4.3.2 AI Model Registry Design**

**4.3.2.1 Federated and Versioned Architecture**

The Nexus AI Model Registry (NAMR) is built on a **federated, containerized model infrastructure**. All models are:

* **Version-controlled**, with model lineage, audit trails, and rollback options;
* **Metadata-rich**, tagged with provenance, use case taxonomy, input features, risk domain alignment, and ethical review status;
* **Containerized**, deployable on sovereign infrastructure, cloud instances, or offline nodes;
* **Federated**, allowing decentralized updates and continuous learning via secure multiparty computation and federated training.

**4.3.2.2 Model Categories**

Models in the registry are classified into multiple thematic domains:

* **Climatic and Environmental Hazards**: drought forecasting, glacial melt detection, cyclone trajectory estimation, wildfire spread
* **Infrastructure Fragility and Urban Risk**: asset vulnerability models, transportation network collapse simulations, power grid fragility indices
* **Public Health and Epidemics**: outbreak forecasting, vaccination logistics optimization, syndemic risk mapping
* **Financial and Economic Shocks**: sovereign risk modeling, insurance pricing, systemic fragility scoring
* **Cascading and Compound Risks**: multi-hazard event chains, fragility feedback loops, cross-sector stress propagation
* **Social and Governance Resilience**: institutional adaptation score modeling, policy impact forecasting, community capacity indices

**4.3.2.3 Local Fine-Tuning and Customization**

To ensure **geopolitical relevance and cultural validity**, GRA members are granted rights to fine-tune base models with local data using:

* Transfer learning pipelines for LLMs and time-series models
* Multilingual embedding adjustment for early warning NLP models
* Reinforcement learning from civic feedback via Nexus Platforms
* Local parameter customization (e.g., taxonomies, units, socioeconomic baselines)

Fine-tuned models retain shared lineage while creating **sovereign variants** hosted under sovereign metadata governance and smart contract–protected IP frameworks.

***

#### **4.3.3 Model Governance and Ethics**

**4.3.3.1 Registration and Certification Process**

All models are required to pass a **three-layer certification protocol** before being published or deployed:

1. **Technical Review:** Verification of algorithmic validity, data integrity, training methodology, performance metrics, and reproducibility.
2. **Ethical Audit:** Screening for bias, discriminatory outcomes, or misuse potential. All models undergo explainability validation (e.g., SHAP, LIME, XAI) and dual-use risk analysis.
3. **Community Feedback Round:** Participatory review involving local experts, Indigenous knowledge holders, civic actors, and youth panels through Nexus Platforms Interface.

Models passing all three layers are published with a **Nexus Model Integrity Badge** and public audit logs.

**4.3.3.2 Model Accountability via NSF**

Each model’s lifecycle is tracked on **NSF**, including:

* Contributor and model steward identifiers (via NXS-NSF Credential)
* Deployment history and access logs
* Version history and update cadence
* Consent records for underlying datasets
* Triggered events, impact flags, and anomaly reports

Smart contracts define usage rights, retraining intervals, performance benchmarks, and deactivation triggers.

***

#### **4.3.4 Nexus Simulation Cloud (NSC)**

**4.3.4.1 Real-Time Risk Simulation Environment**

The Nexus Simulation Cloud (NSC) is a globally distributed, cloud-native compute environment for running risk simulations at various spatio-temporal scales.

**Key Capabilities:**

* Real-time integration with live sensor and EO feeds
* Scenario forecasting with user-defined intervention parameters
* Simulations ranging from localized urban flooding to global food system shocks
* Multilingual visualization of cascading effects, policy options, and resource flows
* Exportable outputs in standardized formats for public dashboards, reports, and alert systems

**4.3.4.2 Use Cases Across Governance Levels**

* **Sovereign Governments:** Test infrastructure policies, simulate climate adaptation pathways, design DRR/DRF interventions
* **Cities and Municipalities:** Visualize compound hazards, heat islands, zoning effects, or smart infrastructure retrofits
* **Enterprises and Insurers:** Run portfolio stress tests, simulate extreme event exposure, align with climate risk disclosures
* **Civil Society and Academics:** Conduct participatory foresight, validate academic hypotheses, simulate social response scenarios

**4.3.4.3 Multi-Agent and Human-in-the-Loop Simulations**

Advanced modules include:

* Agent-based simulations for population displacement, mobility, and social tension
* Human-in-the-loop decision simulations for testing policy reactions under uncertainty
* Counterfactual and “black swan” event modules for long-tail risk awareness
* Immersive foresight chambers using XR/VR interfaces for public policy training and youth engagement

***

#### **4.3.5 Model Contribution and Open Innovation Ecosystem**

GRA encourages members to contribute to the Nexus AI Commons through:

* Open model publication under Nexus Public License (NPL)
* Incentives via Nexus Impact Credits (NICs) for verified social utility
* Co-authorship opportunities for scientific publications, SDG monitoring tools, and foresight policy briefs
* Technical support for model localization, validation, and deployment

All contributions are reviewed through transparent processes involving academic reviewers, ethical auditors, and public participation panels.

## Sources

1. UN General Assembly (2015). Sendai Framework for Disaster Risk Reduction 2015–2030. A/RES/69/283, 3 June 2015. <https://www.undrr.org/publication/sendai-framework-disaster-risk-reduction-2015-2030>
2. United Nations (2021). Our Common Agenda: Report of the Secretary-General. New York: United Nations. <https://www.un.org/en/common-agenda>
3. UN General Assembly (2024). The Pact for the Future. A/RES/79/1, adopted 22 September 2024, with the Global Digital Compact (Annex I) and the Declaration on Future Generations (Annex II). <https://undocs.org/A/RES/79/1>
4. Nexus Standards. NS-0: Constitution and principles. Status: PROPOSED; UNI `NXS-STD-ST-000004`. <https://nexustandards.com/standards/ns-0/>
5. GCRI. GCRI, GRF and GRA. <https://therisk.global/consortium/institutions/>
6. GCRI. GCRI Canada. <https://therisk.global/about/gcri-canada/>
7. [The Global Risks Forum](/organization/institutions/grf.md). GRF in the Consortium. <https://globalriskforum.com/about/consortium-role/>
8. [The Global Risks Alliance](/organization/institutions/gra.md). GRA in the Consortium. <https://globalriskalliance.com/about/consortium-role/>
9. This documentation: [Governance in operation](/organization/governance-in-operation.md); [The Model](/organization/model.md); [historical labels](/organization/reference.md).


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