EM-LND-14 · Landscape · W3
AI and research landscape
Links between research, models, datasets, runs, evaluations, systems and consumed resources.
Partially published; research continues
Claude: complete-frozen-study-and-audit; Grok: complete-browser-study.
Published results
Research note, in Russian: Canonical promotion remains held by the limits published with the profile.
Subject boundary and candidate types
- AIResearchLandscape
- AIUsageNetwork
Deep research questions
- Which systems use a withdrawn artifact?
- Which evaluations have lost applicability?
- How is compute linked to research without a mandatory product?
Verifiable invariants
- A run is not an artifact
- A benchmark is not a universal clearance
- Rights to inputs are preserved
End-to-end acceptance scenario
A withdrawn dataset identifies the affected training and evaluations while keeping separate decisions for deployments.
Negative case
A research checkpoint necessarily creates a commercial product.
Approaches to compare
- Vercy composition and whole-object: a separate landscape object and delegation
- ArchiMate/ISO 42010: views, questions and representation rules
- Compare participant subject models and the practical assembly of a permitted context
Candidates in the live catalogue
- WM-AI-001 · AI System · 0.3.0-research.1 · installable
Semantic fit requires boundary research; a published model does not by itself complete this card. - WM-AI-003 · AI Model Evaluation · 0.3.0-research.1 · installable
Semantic fit requires boundary research; a published model does not by itself complete this card. - WM-AI-006 · Model Training / Fine-tuning Run · 0.3.0-research.1 · installable
Semantic fit requires boundary research; a published model does not by itself complete this card. - WM-AI-008 · AI Safety / Governance Assessment · 0.3.0-research.1 · installable
Semantic fit requires boundary research; a published model does not by itself complete this card.
Result requirements
Every card is executed together with the full research contract: definitions, fields and cardinalities, lifecycle, sources, data mastership, rights, the five object facets, at least eight invariants, positive and negative examples, dependencies, migration and applicability limits.