Step 4: tool results

get_claim_instances

{
  "claim_id": "73fad761-cd72-4aaf-9484-39da8c3558c1"
}

{
  "claim_id": "73fad761-cd72-4aaf-9484-39da8c3558c1",
  "total": 1,
  "limit": 20,
  "offset": 0,
  "has_more": false,
  "instances": [
    {
      "id": "82181a16-ae92-4ffe-8e60-37d1d2df7875",
      "source_id": "0a99fd17-2b29-45c8-9ab6-6afe1fdbc286",
      "verbatim_text": "The error is to treat those choices as invisible and then interpret a narrow confidence band as if it covered instrument, protocol and provenance uncertainty.",
      "context": "Section 8 on dated forecasts.",
      "stance": "affirms",
      "confidence": 0.7,
      "speaker": null,
      "publication": null,
      "source_date": null,
      "link": null,
      "source_title": "Frontier AI Forecasting Has a Measurement Problem: An Audit of Progress Evidence",
      "source_type": "preprint",
      "source_url": "https://arxiv.org/pdf/2608.14903",
      "source_published_date": "2026-08-14",
      "source_authors": [
        "Costa, Fabricio F"
      ],
      "source_publisher": "arXiv.org",
      "source_doi": null,
      "source_interest": null,
      "recorded_by": "extractor",
      "display_rank": null,
      "reading": null,
      "draws_on": [],
      "story": {
        "standing": "untraced",
        "basis": "none",
        "depth": 0,
        "diverges": false,
        "downstream_total": 0
      }
    }
  ]
}