{
  "schema": "certiv_public_ai_discovery_dossier_v1",
  "corpus_id": "certiv-ai-discovery-2026-07-16",
  "reviewed_at": "2026-07-16",
  "evidence_boundary": "These are Certiv-authored test dossiers, not author-issued Certiv receipts. A pinned PDF proves file identity only. A passing selected replay records one bounded observation; it does not independently reproduce a paper's central claim or establish truth, novelty, priority, safety, or correct interpretation.",
  "case": {
    "slug": "verification-in-ai-discovery",
    "case_type": "method-control",
    "domain": "Scientific method",
    "title": "The Need for Verification in AI-Driven Scientific Discovery",
    "authors": {
      "display": "Cristina Cornelio, Takuya Ito, Ryan Cory-Wright, Sanjeeb Dash, and Lior Horesh",
      "count": 5
    },
    "paper": {
      "arxiv_id": "2509.01398",
      "version": "v2",
      "submitted": "2025-09-01",
      "version_date": "2025-12-17",
      "abs_url": "https://arxiv.org/abs/2509.01398v2",
      "pdf_url": "https://arxiv.org/pdf/2509.01398v2",
      "pdf_sha256": "d598af4bcb9b0546314e1718b1e94e506709a225602f315cbb59f62317dd9ce4",
      "pdf_bytes": 2009058,
      "pages": 25,
      "extracted_text_bytes": 86104,
      "parser_observations": [
        "Recognized as a PDF and not encrypted.",
        "pdfinfo reported JavaScript: no.",
        "pdfdetach reported no embedded files.",
        "pdftotext completed successfully."
      ]
    },
    "selection_rationale": "A methodological control included to test whether the corpus itself states a defensible verification boundary rather than optimizing for positive AI-discovery narratives.",
    "claim": {
      "reported": "The authors argue that scalable, reliable verification must be central to AI-assisted scientific discovery.",
      "certiv_observed": "The exact v2 paper was pinned and treated as a methodological control, not as an experimental discovery result.",
      "not_established": "Pinning this review does not prove its historical, economic, or methodological arguments, nor does it validate Certiv's implementation."
    },
    "verification_level": "source-pinned",
    "central_claim_independently_reproduced": false,
    "checks": [
      {
        "id": "pdf-identity",
        "status": "observed",
        "label": "Exact PDF identity",
        "observation": "The downloaded v2 PDF matched the recorded SHA-256, byte count, and page count.",
        "boundary": "This establishes file identity only."
      },
      {
        "id": "method-control",
        "status": "control",
        "label": "Methodological control",
        "observation": "The case is intentionally classified as analysis of verification needs rather than an AI-made discovery.",
        "boundary": "Its inclusion prevents the corpus label from implying that every paper reports a new discovery."
      }
    ],
    "artifacts": [],
    "red_team_findings": [
      "A verification framework must expose unverifiable and blocked cases, not only passing demonstrations.",
      "Computational verification is only one layer; empirical, formal, novelty, and interpretation review can remain outside its scope.",
      "The word verification is overloaded, so every dossier needs an operational statement of what was actually checked."
    ],
    "certiv_mapping": {
      "inputs": "Exact review-paper version.",
      "checks": "Identity and classification control.",
      "receipt_boundary": "methodological control; no discovery claim",
      "missing_for_deeper_verification": "Independent review of the paper's synthesis and any empirical claims it cites."
    },
    "sources": [
      {
        "label": "Exact arXiv record",
        "url": "https://arxiv.org/abs/2509.01398v2"
      }
    ]
  }
}