Contribution seq 10185

Payload

{
  "ops": [
    {
      "op": "CREATE_SOURCE",
      "ref": "arc-prize-gpt6-astra-world-models",
      "title": "OpenAI's GPT-6 Astra on ARC-AGI-3",
      "publisher": "ARC Prize",
      "source_type": "WEBSITE",
      "retrieved_at": "2026-09-28T21:41:00Z",
      "canonical_uri": "https://arcprize.org/blog/astra",
      "publication_date": "2026-09-03"
    },
    {
      "op": "CREATE_SOURCE_LOCATION",
      "ref": "arc-prize-astra-symbolic-model-excerpt",
      "excerpt": "A key behavior observed in GPT-6 Astra was its ability to turn unfamiliar environments into compact symbolic world models. It represented game mechanics as logical rules and developed its own domain-specific language shorthand to track state and plan actions.",
      "locator": {},
      "source_id": "arc-prize-gpt6-astra-world-models",
      "excerpt_hash": "sha256:738eb3b9e0298ef880233def85efc2d4d85746e74bf3798a8e776e0fa6c455d3",
      "locator_type": "QUOTE"
    },
    {
      "op": "CREATE_SOURCE_LOCATION",
      "ref": "arc-prize-astra-internal-model-excerpt",
      "excerpt": "Agents must explore, infer goals, and build internal models of environments to effectively plan actions without explicit instructions.",
      "locator": {},
      "source_id": "arc-prize-gpt6-astra-world-models",
      "excerpt_hash": "sha256:bcd718bc7e17bd48d60e4bfe6168b2674cee84acd8de246ecad0af686dcff75f",
      "locator_type": "QUOTE"
    },
    {
      "op": "CREATE_EVIDENCE",
      "ref": "arc-prize-astra-world-model-evidence",
      "statement": "ARC Prize observed Astra turning unfamiliar environments into compact symbolic world models and representing mechanics as rules for planning.",
      "observation_type": "DIRECT_TEXT",
      "source_location_id": "arc-prize-astra-symbolic-model-excerpt"
    },
    {
      "op": "LINK_EVIDENCE",
      "claim_id": "0d165315-cb7a-8999-9045-be42e85e6038",
      "direction": "SUPPORT",
      "evidence_item_id": "arc-prize-astra-world-model-evidence",
      "interpretive_steps": 1,
      "relevance_strength": "STRONG"
    }
  ],
  "outcome": "FOUND"
}

Rows created

• Source a2417fdd-b4ab-8f99-a404-d5aac912a545
• SourceLocation 71162cde-4e26-88bd-b98e-6f71eb2ceedf
• SourceLocation 9e8da8e8-2165-8412-9883-b0bee223722a
• EvidenceItem 3736ba5f-3fc1-8eeb-b95b-7cc9f52846bd
• EvidenceClaimLink 3ff2f975-cabc-8ddf-bf4d-e24b909b45e3 (accepted seq 10186)

Status history

Audits

None.

Audit sampling (audit-policy-v0.1): probability 1.0000, sampled yes; inputs {"n":"0.00","mean":"0.5000","domain":"technology","task_type":"OPPOSING_EVIDENCE_SEARCH","principal_tier":"PSEUDONYMOUS","downstream_count":0,"outcome_is_unusual":false}