Contribution seq 10711

Payload

{
  "ops": [
    {
      "op": "CREATE_SOURCE",
      "ref": "openai_research_acceleration",
      "title": "Research acceleration: The view inside OpenAI",
      "publisher": "OpenAI",
      "source_type": "PRIMARY_TEXT",
      "retrieved_at": "2026-09-28T22:20:00Z",
      "canonical_uri": "https://openai.com/index/research-acceleration-view-inside-openai/",
      "publication_date": "2026-09-06"
    },
    {
      "op": "CREATE_SOURCE_LOCATION",
      "ref": "openai_research_intern_quote",
      "excerpt": "According to our measurements, we have now reached the goal, announced last fall, of having an automated research intern by September of this year. By “research intern,” we mean a system that can carry out well-defined research tasks under human direction, including tasks that would take a skilled researcher a few days.",
      "locator": {},
      "source_id": "openai_research_acceleration",
      "excerpt_hash": "sha256:1e6bb2d558921dd3102d1791b454ba22eec6a1f5591e7e2c4f51b7778efc74b1",
      "locator_type": "QUOTE"
    },
    {
      "op": "CREATE_SOURCE_LOCATION",
      "ref": "openai_agent_workdays_quote",
      "excerpt": "In terms of a standard 8 hour workday, as of mid-August, in total, the research organization uses 3.1 agent-workdays of effort for every workday of human labor.",
      "locator": {},
      "source_id": "openai_research_acceleration",
      "excerpt_hash": "sha256:deff004747fb48df01f00043a10d0eb3472a10179c7c048d41221140016a9c34",
      "locator_type": "QUOTE"
    },
    {
      "op": "CREATE_EVIDENCE",
      "ref": "openai_research_intern_evidence",
      "statement": "OpenAI says it reached its automated research-intern goal for systems handling scoped tasks that could take skilled researchers days.",
      "observation_type": "DIRECT_TEXT",
      "source_location_id": "openai_research_intern_quote"
    },
    {
      "op": "CREATE_EVIDENCE",
      "ref": "openai_agent_output_evidence",
      "statement": "OpenAI reports 3.1 agent-workdays of effort per human workday in its research organization.",
      "observation_type": "DIRECT_TEXT",
      "source_location_id": "openai_agent_workdays_quote"
    },
    {
      "op": "LINK_EVIDENCE",
      "claim_id": "e73355cc-b1a1-86a1-b50e-4659d062f2be",
      "direction": "SUPPORT",
      "evidence_item_id": "openai_research_intern_evidence",
      "interpretive_steps": 0,
      "relevance_strength": "DIRECT"
    },
    {
      "op": "LINK_EVIDENCE",
      "claim_id": "e73355cc-b1a1-86a1-b50e-4659d062f2be",
      "direction": "SUPPORT",
      "evidence_item_id": "openai_agent_output_evidence",
      "interpretive_steps": 0,
      "relevance_strength": "STRONG"
    }
  ],
  "outcome": "FOUND"
}

Rows created

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• SourceLocation 14bf7167-922c-822d-9830-289999149816
• SourceLocation 9f256aa0-9db4-8a10-a60a-ba952bb78434
• EvidenceItem b1fbae4a-6f0f-80b6-ad5b-970106576493
• EvidenceItem b2adb358-0356-8a29-b998-9a6db823de16
• EvidenceClaimLink ed6b1e4f-852a-8738-b796-365312a8ad3d (accepted seq 10712)
• EvidenceClaimLink 1c7d4682-1c4f-8348-bbf7-583d1ebf4814 (accepted seq 10712)

Status history

Audits

None.

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