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Global Risks Index

The Global Risks Index · Methods · model registry 1.0.0

Every risk method, standardised

670 methods across hazard science, exposure, vulnerability, loss, catastrophe, financial, sovereign, systemic, climate, health, cyber and assurance, each with a stable ID, an honest implementation state and the standards that govern it.

Page GRX-MTHEdition Baseline Edition 2026Evidence close 2026-09-30Values not yet publishedMethod v1.0.0-draft
670
methods
23
fabrics
169
kernel-bound
48
connected or reference

01Fabrics

23 method fabrics

Every quantitative method the index and its platform may use is registered once, in one fabric, with a stable capability ID; a title is display text only.

Fabric Capabilities Kernel-bound Planes মানদণ্ড
Universal mathematics and statistics 38 26 Julia, TypeScript
Hazard science 37 7 Julia, Python
Exposure and asset intelligence 18 4 TypeScript, Python, SQL
Vulnerability, fragility and resilience 19 8 Julia, Python
Consequence and loss 18 6 Julia, Python, r
Catastrophe risk 23 13 Julia, Python, r
Networks, dependency and systemic risk 21 10 Julia, Python
Financial risk 57 13 Julia, Python, r
বিমা ও পুনর্বিমা 38 14 r, Julia
Markets, trade and supply chains 30 7 Julia, Python
Sovereign, macroeconomic and development risk 28 5 Julia, Python, r
Policy, regulation and governance 17 1 Python, Julia
Water risk 26 7 Julia, Python
Food, agriculture and fisheries 25 2 Python, Julia
Energy risk 26 7 Julia, Python
Health and epidemiology 25 9 Julia, Python, r
Climate, nature and biodiversity 24 3 Python, Julia
Critical infrastructure and industrial risk 27 6 Julia, Python
Cyber, AI and frontier technology 56 6 Python, rust, Julia
Geopolitics, conflict and human security 21 5 Python, Julia
Projects, programmes and infrastructure investment 27 2 Julia, Python
Risk data 24 0 TypeScript, Python, rust, SQL
Scientific assurance 45 16 Julia, Python, r, rust
02State

What is implemented

169 capabilities are bound to hand-written scientific kernels with golden-value tests in Python, Julia or R. Every capability is release-held, with a supported claim level of integrated.

model registry 1.0.0 · 670 capabilities
Connected9
Reference implementation39
Adapter required327
Specialist model required159
Data required136
Kernel bindings by plane
Python161
Julia4
r4
Connected
An existing governed engine path is available; specialist physics still needs validation for the context of use.
Reference implementation
Transparent reference mathematics for diagnostics and parity, not institutional-grade calibration.
Adapter required
Registered; an execution adapter is still to be built. Requests fail closed.
Specialist model required
Needs a specialist domain model. Requests fail closed rather than fabricate an output.
Data required
Needs governed data that is not yet available. Requests fail closed.
03Contract

What every method must carry

The same contract applies to an NXS-GRX (canonical data, provenance and risk) index, a custom index in Index Studio and a model run in Model Lab.

প্রমাণ
sealed RiskDataCut for data-grounded execution; source release and exact-record lineage; rights/purpose decision; chronotope; model/method version; uncertainty and applicability evidence
Uncertainty
aleatory where applicable, epistemic, parameter, model-form, data, scenario
Verification and validation
verification, calibration or justification, validation or benchmark, applicability, reproducibility
ফলাফল
uncertainty-packet, evidence-envelope, vvuq-receipt
Refusals
NO_DATA_IS_NOT_ZERO NO_UNGROUNDED_MONETARY_TRUTH NO_FAKE_SPATIAL_MATERIALIZATION NO_CAUSAL_CLAIM_WITHOUT_IDENTIFICATION NO_CALIBRATION_CLAIM_WITHOUT_EVIDENCE NO_AUTHORITY_ESCALATION
04Honesty

What registration does not mean

  • Capability registration is not model execution, calibration, observation, validation or assurance.
  • CONNECTED means an existing governed engine path is available; specialist domain physics still requires context-of-use validation.
  • IMPLEMENTED_REFERENCE means transparent reference mathematics exists for diagnostics/parity, not institutional-grade calibration.
  • SPECIALIST_MODEL_REQUIRED and DATA_REQUIRED fail closed rather than fabricate outputs.
  • Cryptographic integrity proves the network's own records relationships, not scientific truth.

Form

Comment on the methodology

Open consultation on normalisation, weighting, aggregation, imputation, uncertainty and validation; every comment receives a disposition in the consultation record.

  1. 01Fill inFields marked (required) are needed; everything else helps the review.
  2. 02ReferenceYou get a reference on screen; the record is kept in this site’s WordPress database.
  3. 03ReviewThe outcome is recorded in public. Contact details stay on this site and are never published or shared.
Form · grx-consult

This form opens here once it is switched on. Until then, send it through the Nexus Reports gateway.

Propose a method

New methods are registered with a stable ID, a hand-derived golden test and their evidence obligations before any page uses them.