Encevra Research Round 44: This Record Fails, or No Record Exists? Record Level Status Ledgers, Completeness Records, and Independently Reviewed HOLD Labels
Round 44 of Encevra Research tests whether AI contract readers stop reading a defective record as proof that no valid record exists when the evidence ledger records what each record shows and asks, separately, whether anything excludes other records, and it puts every authored abstention label through a blind independent review. Eight new authored contract families are each written in three variants: K, in which the records satisfy the requirement; T, a near miss that fails one stated requirement; and TC, the near miss plus a record stating the file is complete. A structural diagnostic (E44-A, no model calls) certifies the variants, the HOLD labels, the resolver contrast, and 24 new SEC EDGAR exhibits. Live (E44-B), Witness A agreed blind with 48 of 48 labels and reported packet defects in 6 of 8 families. Record level ledgers by Witnesses B, C, and D released an unsafe FAIL on 1 of 24 near miss readings, against 12 of 16 for the unchanged condition ledger and 8 of 16 for declared open direct readers on the same items, where both witnesses erred on the same four. All 24 completeness record ledgers and all 16 direct readings resolved to FAIL. Two witnesses over held requirements met only by two records together. On the SEC exhibits (E44-C, 144 calls), no flag only or rewriting validator made an unsafe release; flagging caught every near miss seed but left 12 false holds per witness, and rewriting repaired all 48 seeded ledgers while a pre registered gate routed 24 repairs to review. Phases first stopped by the run budget were completed the same day with unchanged settings, after first results were seen. The round revises proposition P7, extends P1, and refines P5. Manuscript: https://research.encevra.com/round-44. Experiments: https://research.encevra.com/experiments.
Authors
- Ben Wilkins (ORCID: https://orcid.org/0009-0005-6532-3200)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-11-02
- DOI
- https://doi.org/10.5281/zenodo.23883769
- Primary Topic
- Artificial Intelligence in Law
- Type
- preprint