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Release planning · no model scores

AA-Omniscience and AA-LCR evidence mapping

Exact V3 collection, facet, metric, lineage, identity and rights mapping for AA-Omniscience and AA-LCR from Artificial Analysis.

V3 evidence records

1 collection mapping

A repeated upstream benchmark can map to several collections. Each record below preserves its own task role, facets, capability atoms, subject identity, metrics, lineages and exclusions.

supporting evidence · summarization-grounding/artificial-analysis/aa-omniscience-and-aa-lcr

Summarization & Grounded Knowledge

Which models are best at summarization and grounded knowledge work?

Upstream access
machine-ready
Eligibility
runnable-now
Registry
registered
Max task directness
45%

Collection facets

  • Meeting notes · hybrid · 25%

    Capture decisions, owners, deadlines, and unresolved items.

  • Long-document summaries · hybrid · 25%

    Preserve important coverage and caveats across long source material.

  • Grounded question answering · hybrid · 25%

    Answer only from supplied evidence and expose insufficient support.

  • Factual consistency · objective · 25%

    Avoid contradictions, invented details, and attribution drift.

Capability atoms

non_hallucinationlong_context_reasoning

Subject identity

Declared:
foundation-model
Metric partitions:
foundation-model
Separate partition required:
no
Identity projection:
forbidden

Usable evidence lineages

  • aa-omniscience/foundation-model
  • long-context-reasoning/foundation-model

Exact metric contract

MetricLineageSubjectProtocolUse
aa_omniscience_non_hallucination_rateAA-Omniscience Non-hallucination Rateaa-omnisciencefoundation-modelnot suppliedusable
aa_lcrAA-LCRlong-context-reasoningfoundation-modelnot suppliedusable

Exclusions and blockers

  • source redistribution is conditional: assumed

Mapping note

Do not count AA aggregate and component fields together.