# Batch 01 Review

## Review Metadata

- Batch ID: `2026-05-17-batch-01`
- Case ID: `case-public-sector-ai-policy-audit-001`
- Arm ID: `full_ofone`
- Run ID: `2026-05-17-batch-01__case-public-sector-ai-policy-audit-001__full_ofone__agentic_coding__r1`
- Reviewer: local Codex unblinded review
- Review date: 2026-05-18
- Blinding status: `unblinded`

## Pre-Score Compliance Gate

| Check | Result | Notes |
| --- | --- | --- |
| Case fidelity | `pass` | Artifact identity and artifact-level benchmark trace bind to `case-public-sector-ai-policy-audit-001`, the full-OfOne prompt, and the expected input-bundle hash. |
| Required outputs present | `pass` | The run includes raw Markdown output, Audit artifact JSON, validator JSON, rendering, patch report, and review file. |
| Independence from other arms/examples | `pass` | The artifact is case-native and does not reuse another case artifact or other benchmark arm output. |
| No-superiority compliance | `pass` | Makes no method-performance or empirical superiority claim. |
| Auto-reject before aggregate scoring | `no` | No pre-score gate row failed. |

## Semantic Fidelity

- Case binding: Pass; artifact_identity.case_id and benchmark_trace values match the case file, prompt file, and input-bundle hash.
- Copied-example risk: Low; the artifact content is scoped to the public-sector AI policy audit case.
- Evidence provenance adequacy: Adequate for the abstract benchmark case; evidence is bound to the frozen case file and full-OfOne prompt, with explicit scenario-level caveat.
- Artifact/source identity: Artifact, run ID, case ID, prompt hash, input-bundle hash, validator, rendering, patch report, and review file align with the run record.

## Scores

| Metric | Score | Rationale |
| --- | ---: | --- |
| decision_quality | 4 | Correctly blocks live deployment and returns the policy for model, rights, and review evidence. |
| evidence_grounding_precision | 4 | Uses stable content hashes, evidence identities, and separates case evidence from local interpretation. |
| uncertainty_calibration | 4 | Open unknowns block release and rendering confidence without overstating deployability. |
| trace_completeness | 5 | Links evidence, claims, unknowns, criteria, actors, gates, review logs, triggers, and rendering. |
| auditability | 5 | Includes artifact identity, benchmark trace, computed validator JSON, Audit rendering, patch report, and review file. |
| update_quality | 4 | Trigger activation reaches gates, claims, options, review logic, tradeoff surface, and rendering. |
| cost | 2 | Full artifact and review burden is materially higher than text-only arms. |
| inter_run_stability | NA | Only one repeat has been reviewed for this case/arm/model family. |

## Required Notes

- Strongest decision-relevant contribution: Turns rights, legitimacy, model evidence, stakeholder exposure, gates, review logs, and patch closure into addressable state.
- Most important unsupported claim or missing evidence: The benchmark dossier lacks real external policy, model validation, subgroup, appeal-access, and operational monitoring artifacts.
- Hidden variable or unknown that changed the review: Symbolic review and automation bias can undermine a nominal human-in-the-loop policy.
- Gate, safety, or release concern: Gate G1 and G2 remain open and returned for evidence, blocking release.
- Patch/update behavior, if applicable: Trigger T1 expands through the human-review gate; T2 supports scoped rerun on new evidence; T3 patches claim conflict.
- Failure mode observed: No case-binding failure; remaining limitation is scenario-level evidence rather than a real policy dossier.

## Adjudication

- Accept run for aggregate scoring: `yes`
- If no, reason: N/A
- Reviewer confidence: `medium`