{"claim":{"id":"12e6bb62-75b6-42a8-81bd-036ecc657b68","submission_id":"b6b345a7-f499-47b1-bb9d-5ad3d05ea415","submission_revision_id":"372633e3-e694-4dc9-9281-8f0da491e6cc","builder":"builder-01","status":"active","claimed_at":"2026-10-15T15:13:19.989078Z","delivered_at":null,"ended_at":null,"delivery_note":null,"end_reason":null},"task":{"submission_id":"b6b345a7-f499-47b1-bb9d-5ad3d05ea415","submission_revision_id":"372633e3-e694-4dc9-9281-8f0da491e6cc","revision_version":1,"submission_status":"under_review","submitted_at":"2026-08-27T20:16:52.216097Z","submitter_name":"Thorben Jansen","submitter_email":"tjansen@ipn.uni-kiel.de","task":{"status":"submitted","version":1,"extra_fields":{"difficulty_self_test":{"model":"GPT-5.5","harness":"Codex","estimated_score":"<1%"}},"submitted_at":"2026-08-27T20:16:52.216097+00:00","industry_domain":"Educational Assessment / Learning Analytics","task_short_name":"pisa_raw_process_forensics_hard25_v1","operating_system":"Linux","task_description":"Professional Context: Large-scale educational assessments such as PISA record detailed interaction data while students compose written responses. Assessment data engineers, learning-analytics specialists, and psychometric researchers need to reconstruct the text directly from these raw process records to assess text quality at every time point. This task uses unpublished authentic writing-process data from approximately 15-year-old students participating in a PISA large-scale assessment.\n\nObjective: Recover the exact final contents of the writing field for 25 authentic PISA writing sessions. For each case, reconstruct the student’s final submitted text exclusively from the supplied raw process record and save it as a byte-identical UTF-8 text file. Every character and byte must be preserved exactly, including spelling, punctuation, whitespace, line endings, Unicode representation, and terminal-newline state.\n\nStarting State: Treat the relevant writing field as initially empty. For each case, the agent receives one complete outer JSON record copied verbatim from the original PISA writing-process archive. The records retain their original nested representation and embedded log payloads. They have not been decoded, filtered, normalized, reordered, or converted into a simplified event stream. The submitted end texts are hidden.\n\nInput Materials: evaluation_manifest.jsonl maps 25 public case IDs to cases/<case_id>.raw.jsonl. Each raw file contains one complete original outer JSON record. The training/ directory contains two person-disjoint worked cases from outside evaluation, each with its complete raw record and a byte-for-byte copy of its existing curated end text.\n\nInstructions and Rules: Determine which assessment item and process stream represent the relevant writing task, decode the recorded interactions, and reproduce the final state of its writing field. No decoded event schema, decoder, replay implementation, application source code, or event-semantics guide is supplied. Infer the necessary structure and transformations from the complete raw records and the two worked examples. External services are not required.\n\nRequired Output: Create submission/<case_id>.final.txt for every evaluation case. Use UTF-8 without BOM. Preserve every byte, including whitespace, line endings, Unicode representation, and terminal-newline state. Do not correct spelling or grammar. Do not include Markdown, explanations, metadata, hashes, or commentary. submission/ must contain exactly the 25 required .txt filenames.\n\nGround Truth: Every hidden reference file is a direct byte-for-byte copy of a curated submitted end-text file. Replay output is used only to establish eligibility and reproducibility.","software_licensing":"Free/Open Source","evaluation_criteria":null,"verification_method":"Run python3 score_submission.py <submission_directory>. Submission structure is valid only when exactly the 25 required .txt filenames are present. A case receives one point only when its complete predicted byte sequence equals the corresponding hidden existing end-text file; otherwise it receives zero. Final score is byte-exact files divided by 25. No Unicode, whitespace, line-ending, spelling, or semantic normalization is permitted. The reference package includes perfect and empty scoring controls, the canonical evaluator-only raw-data decoder, full source and hash provenance, the deterministic three-run selection ledger, and a validator that reconstructs all 27 evaluation and training outcomes exactly.","software_and_version":"Python 3.11+ and a UTF-8-capable text-processing environment","specific_requirements":null,"expected_completion_time":null},"files":[{"file_id":"745a79a0-eb1b-4f73-a148-04b9f6046c56","filename":"pisa_raw_process_forensics_hard25_v1_participant.zip","category":"input_materials","content_type":"application/zip","size_bytes":8614428},{"file_id":"4c94e2c0-458e-495e-85cd-06edb00ccc83","filename":"pisa_raw_process_forensics_hard25_v1_reference_and_provenance.zip","category":"reference_output","content_type":"application/zip","size_bytes":8671154},{"file_id":"81930e0e-c6bf-4034-b7a8-575e2e4a7f1c","filename":"pisa_raw_process_forensics_hard25_v1_exact_package_self_review_evidence.zip","category":"difficulty_self_test_evidence","content_type":"application/zip","size_bytes":183299}],"deep_review":{"overall_verdict":"Strong Accept","review_text":"**Overall Verdict:** Strong Accept — The submission is complete, professionally scoped, byte-exactly verifiable, and fully reachable with strong provenance and solver/reference separation.\n\n**Completeness Check:**\n- Instruction: Complete — Clearly defines the initial state, reconstruction objective, permitted evidence, exact filenames, UTF-8 encoding, and byte-preservation requirements.\n- Inputs: Complete — Includes 25 valid single-record JSONL cases, consistent manifests, and two distinct worked examples with matching hashes.\n- Toolchain: Complete — Requires only freely obtainable Python 3.11+ and standard UTF-8 processing on Linux, with no external services.\n- Reference output: Complete — Contains 25 hidden gold files, provenance hashes, selection records, scoring controls, and reproducibility evidence; gold is absent from participant materials.\n- Rubric: Complete — Awards one point per byte-identical file, divides by 25, checks required filenames, and explicitly prohibits normalization or partial credit.\n\n**File and Task Reachability:**\nAttachment classification: `reachable`. Task classification: `reachable`. All three manifest attachments were inspected: `pisa_raw_process_forensics_hard25_v1_participant.zip`, `pisa_raw_process_forensics_hard25_v1_reference_and_provenance.zip`, and `pisa_raw_process_forensics_hard25_v1_exact_package_self_review_evidence.zip`. Their downloaded sizes matched the manifest; each was a readable, unencrypted ZIP containing only safe regular-file paths and passing archive integrity checks. Inspection covered the participant instructions and manifests, all 27 raw JSON records, both training texts, all 25 gold files, provenance and selection ledgers, evaluator source and reports, all 25 self-review outputs, and the self-review PNG. No relevant attachment content was left unreviewed. All raw and declared hashes matched, the participant tree matched its evaluator-bundle copy, all records parsed, and an independent safe replay reconstructed all 27 outcomes byte-exactly without finding direct final-text leakage. The declared Python runtime was unavailable in the review environment, and uploaded programs were therefore inspected as inert source rather than executed; this does not affect task reachability. A solver can infer the event representation from the two worked examples, replay each raw record into 25 UTF-8 files, and be evaluated through strict filename and raw-byte comparison. 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.\n\n**Special Screening:**\nNone\n\n**Recommended Changes:**\nThe submission provides coherent instructions, authentic inputs, strong hash provenance, deterministic selection evidence, hidden references, and objective controls. No changes are required.","reviewed_at":"2026-08-27T20:27:45.760807Z"},"claim":{"id":"12e6bb62-75b6-42a8-81bd-036ecc657b68","submission_id":"b6b345a7-f499-47b1-bb9d-5ad3d05ea415","submission_revision_id":"372633e3-e694-4dc9-9281-8f0da491e6cc","builder":"builder-01","status":"active","claimed_at":"2026-10-15T15:13:19.989078Z","delivered_at":null,"ended_at":null,"delivery_note":null,"end_reason":null}},"revision_is_current":true}