---
conjecture: r3-b1-40
family: codex
model: "gpt-5.6-sol (codex-cli 0.144.0-alpha.4, ChatGPT-subscription auth)"
model_stamp_corrected: "2026-08-07 — archives were first written stamped gpt-5.5 by a runner bug (the stamper read config.toml's default instead of the -m flag actually passed). The calls themselves ran on gpt-5.6-sol throughout; only the label was wrong. Corrected in place, noted here rather than silently."
received: 2026-08-07
template: PROMPT_TEMPLATE_v1.md sha256 4344aabfacfe88362c56d89b6c89d594a7bf3a221e18a16b0e351482447e512f
rivals_parsed: 3
validation: VALID
---

{
  "rivals": [
    {
      "mechanism": "A common portal-ingestion pipeline used for the completed-state inventories discarded or never mapped folio counts into the portal's dedicated field. The small positive fraction came from records loaded through a different importer or entered manually.",
      "why_it_explains_the_same_evidence": "If the 11 training states and nine holdouts were predominantly loaded through the same lossy pipeline, exact zeros and uniformly sub-0.5% rates follow even when the harvesting code correctly captures every field exposed by list pages. The concentration of positives outside the training states is also expected if importer or ingestion-batch membership is geographically clustered.",
      "named_confounds": [
        "portal-ingestion pipeline",
        "schema-version mismatch",
        "state or institution ingestion-batch confounding"
      ],
      "discriminating_test": {
        "description": "For a stratified sample of harvested records, retrieve the raw detail-page or record-API response and inspect the dedicated folio field, then stratify results by institution, import date, record-ID range, and any schema or batch marker. The stated mechanism predicts some values present in raw detail records but absent from list-derived output; the rival predicts that the dedicated field is already absent in the portal record and that nullness changes at importer or batch boundaries.",
        "computable_on_held_data": true,
        "what_result_favors_rival": "The raw detail/API records remain blank in the dedicated folio field, while rare populated records cluster sharply by importer, schema version, institution, or ingestion batch."
      }
    },
    {
      "mechanism": "Folio counts are present in the catalogue but conventionally encoded in free text or another physical-description field rather than the dedicated folio/leaf-count field. Only a small set of institutions or imports maps them into the measured field.",
      "why_it_explains_the_same_evidence": "A stable semantic-mapping convention across the completed states would make the measured field exactly or nearly always blank in both training and holdout data, regardless of harvest completeness. The nationwide 0.27% can arise from exceptional catalogues that use the dedicated field correctly.",
      "named_confounds": [
        "field-semantic mismatch",
        "free-text encoding of extent",
        "institution-specific metadata mapping"
      ],
      "discriminating_test": {
        "description": "Retrieve all available detail metadata for a stratified sample and search alternate fields for validated folio expressions such as leaf counts, folio abbreviations, and recto-verso notation. Compare the prevalence of validated counts in alternate fields with the dedicated-field prevalence. This can be performed by re-querying and extending the same catalogue extraction.",
        "computable_on_held_data": true,
        "what_result_favors_rival": "Validated folio counts occur materially more often in alternate or free-text fields while the dedicated field remains blank; the stated list-parser mechanism instead predicts that counts should chiefly appear in the dedicated field on detail records."
      }
    },
    {
      "mechanism": "Conditioning on a state being completely walkable selects portal partitions built from skeletal bulk inventories, whereas richer records carrying folio counts disproportionately reside in incomplete, unfaceted, or separately indexed partitions. The replication across holdouts then repeats the same selection rule rather than testing an independent metadata regime.",
      "why_it_explains_the_same_evidence": "Every training and holdout unit entered the analysis only after a complete, reconciled state walk. If walk completeness is associated with ingestion architecture or metadata richness, all selected states can remain below the ceiling while the portal-wide positives are concentrated among records or partitions that fail that selection criterion.",
      "named_confounds": [
        "conditioning on walk completeness",
        "state-facet coverage bias",
        "index or shard selection",
        "administrative classification artifact"
      ],
      "discriminating_test": {
        "description": "Without requiring complete enumeration, draw reproducible random or interval samples from incomplete state facets, institution facets, global search results, and unfaceted record-ID ranges; retrieve their raw detail records and compare dedicated-field population rates and metadata richness with records from complete states. Also test whether populated records are disproportionately missing from the union of reconciled state walks.",
        "computable_on_held_data": true,
        "what_result_favors_rival": "Incomplete or unfaceted partitions show substantially higher folio-field population, potentially exceeding 0.5%, and populated records are systematically underrepresented in complete state walks. A pure list-field omission should not make underlying detail-record population depend strongly on whether a state walk can be reconciled."
      }
    }
  ],
  "no_viable_rival": false,
  "notes": ""
}
