**Overall Verdict:** Strong Accept — The submission is complete, internally consistent, objectively evaluable, and supported by unusually thorough process-level provenance.

**Completeness Check:**
- Instruction: Complete — clearly defines the 20-case task, exact passage objective, zero-based half-open offsets, nonoverlap rules, and JSONL deliverable.
- Inputs: Complete — includes 20 held-out texts and 40 balanced, participant-disjoint training cases with labels and complete decoded process histories.
- Toolchain: Complete — Python 3.9+, standard-library JSON processing, and ordinary local archive utilities provide a feasible single-machine workflow.
- Reference output: Complete — includes 81 exact gold passages, case summaries, token decisions, transfer audits, replay inputs, provenance ledgers, validation reports, scoring code, and reproduction code.
- Rubric: Complete — the primary all-or-nothing document metric is precise, with strict passage, word-level, tolerant-passage, and AI-share diagnostics plus verified perfect, all-AI, and no-AI controls.

**File and Task Reachability:**
The attachment set is `reachable`, and the end-to-end task is `reachable`. All four manifest attachments were inspected: `pisa_writing_fragmented_authorship_ale_20_v1_participant.zip`, `pisa_writing_fragmented_authorship_ale_20_v1_reference_and_provenance.zip`, `pisa_writing_fragmented_authorship_ale_20_v1_gpt55_agent_solutions_only.zip`, and `selftest_primary_outcome_0_of_20.png`. Their formats and byte counts match the manifest; all archives are readable, unencrypted, bounded in expansion, and free of unsafe paths or links. Every structured file parsed successfully. Independent checks confirmed 20 unique evaluation cases, 40 balanced training cases, zero source-participant overlap, 81 valid nonoverlapping gold spans, exact substring consistency, the stated 40–70% AI-share range, and sealed participant/reference separation. All three self-test submissions are structurally valid and independently yield 0/20 exact documents, consistent with the screenshot.

No manifest attachment was left unreviewed. Large student-text and event-log contents were structurally validated and sampled rather than manually interpreting every event. Uploaded Python was inspected statically but not executed under safe-review rules; the packaged PASS reports and cross-file invariants independently support the claimed reproduction and controls. A solver can analyze the participant-visible training data, produce the required 20-row JSONL, and be evaluated deterministically against the sealed gold package on one ordinary machine.

License keys, accounts, tokens, and other credentials are not required from the contributor. Confidential, proprietary, or internal material may be evaluated as submitted evidence without requiring additional disclosure.

**Special Screening:**
None — the supplied evidence affirmatively describes authentic, unpublished assessment responses and process records rather than synthetic core data. Public identifiability was not independently searched outside the submitted evidence boundary.

**Recommended Changes:**
The submission already provides a complete solver package, sealed evaluator package, process-level provenance, leakage controls, baseline controls, and consistent self-test evidence. No changes are required.