{"claim":{"id":"a982bd7e-2060-4760-8918-e2885da626d2","submission_id":"167fb43c-078e-4b24-a766-ef24def939c8","submission_revision_id":"f91e187d-e717-455e-b611-b82111e3f19a","builder":"builder-01","status":"active","claimed_at":"2026-10-15T15:29:34.765538Z","delivered_at":null,"ended_at":null,"delivery_note":null,"end_reason":null},"task":{"submission_id":"167fb43c-078e-4b24-a766-ef24def939c8","submission_revision_id":"f91e187d-e717-455e-b611-b82111e3f19a","revision_version":5,"submission_status":"under_review","submitted_at":"2026-09-19T07:13:13.238913Z","submitter_name":"Xingda Lyu","submitter_email":"xlyu18@uw.edu","task":{"status":"submitted","version":5,"extra_fields":{"difficulty_self_test":{"model":"GPT-6 Astra (High); GPT-5.6 Sol (Extra High)","harness":"Codex CLI 0.153.4","estimated_score":"<1%"}},"submitted_at":"2026-09-19T07:13:13.238913+00:00","industry_domain":"Mathematical & Operations Research — Sports League Scheduling","task_short_name":"synthetic_league_new_season_instance_1","operating_system":"MacOS","task_description":"Objective:\nAct as the scheduling analyst for the synthetic 16-team league specified in season.xml. Deliver a complete season timetable that satisfies all mandatory requirements, then improve home-game balance and the spacing between return fixtures. The professional capability assessed is turning interacting scheduling requirements into a usable, conflict-free timetable. A schedule with missing fixtures, team conflicts or violations of mandatory restrictions cannot be used under the supplied rules; preference quality matters only after those requirements are met.\n\nStarting state:\nThe input package contains season.xml, TASK.md, evaluate.py and scoring.json, together with tool and licensing information. These files provide the complete instance, output specification, acceptance rules and scoring formula. Team and round identifiers are zero-based.\n\nThis is a constructed professional scheduling exercise derived from the openly licensed QOBLIB/ITC2021 sports-timetabling structure. It is not a historical or commissioned league season. Its construction and relationship to public source material are documented in the reference package and summarized in the verification field.\n\nInstructions and rules:\n\nSchedule exactly 240 games across 30 rounds. Every team must play every other team once at home and once away, and every team must appear exactly once in each round.\n\nEach unordered pair of teams must meet once in rounds 0–14 and once in rounds 15–29.\n\nSatisfy every HARD restriction in season.xml. These include home/away game counts in designated rounds, counts against designated opponent groups, sliding-window limits, group game-count limits and home/away break limits. TASK.md and the supplied evaluator specify their exact counting conventions.\n\nAmong feasible timetables, minimize the published soft penalty: cumulative home-game imbalance plus insufficient separation between return fixtures. Use the definitions and fixed quality target in TASK.md and scoring.json.\n\nYou may use any available algorithm, software or public resource, including installing optimization tools. Validate the deliverable using the supplied evaluator: python evaluate.py schedule.json.\n\nRequired output:\nSave schedule.json as a JSON object with a \"games\" array of exactly 240 integer triples [home_team_id, away_team_id, round_id]. Submit the actual timetable. A proposed solving method, partial timetable or unsupported infeasibility claim does not fulfill the task.\n\nA verified feasible reference exists. Any timetable satisfying the mandatory rules is eligible for credit, and any feasible timetable meeting or improving the fixed preference target receives full credit. The timetable does not need to match the private reference fixture by fixture. Global optimality is not required.","software_licensing":"Free/Open Source","evaluation_criteria":null,"verification_method":"Run the supplied, frozen evaluator against the submitted schedule.json using the accompanying season.xml and scoring.json. From the directory containing these supplied files, run:\n\npython evaluate.py /path/to/schedule.json\n\nThe evaluator requires only Python’s standard library and returns one official score in [0, 1]. Verification is deterministic and uses no LLM judge. Evaluate the candidate directly against the published constraints and objective; do not require an exact match to the private reference schedule.\n\nOutput validity and completeness\n\nThe candidate must be a JSON object with a \"games\" array containing exactly 240 integer triples [home_team_id, away_team_id, round_id]. Team IDs are 0–15 and round IDs are 0–29. Boolean values are not accepted as integers. The file must not exceed 2,000,000 bytes.\n\nEvery directed opponent pair must occur exactly once. Each team must play exactly once per round, and each unordered opponent pair must meet exactly once in rounds 0–14 and exactly once in rounds 15–29. Self-matches, duplicate fixtures, missing games and team-round conflicts are invalid.\n\nMandatory feasibility\n\nEvery HARD constraint in season.xml must pass, including CA1–CA4 count restrictions and BR1–BR2 home/away break restrictions, using the counting conventions in TASK.md and evaluate.py.\n\nA missing, malformed, incomplete or infeasible timetable receives 0.0. Individually satisfied constraints do not earn separate points because the required deliverable is a complete timetable usable under all stated mandatory rules. This feasibility gate does not depend on resemblance to the reference schedule.\n\nPartial and full credit for feasible timetables\n\nFor a feasible timetable, compute soft penalty C as the sum of two equally weighted components:\n\n1. Home-game balance: For every unordered team pair, calculate the maximum absolute difference between their cumulative home-game counts over all 30 round prefixes. Add max(0, maximum_difference - 2).\n\n2. Return-fixture spacing: For every unordered opponent pair meeting in rounds a < b, add max(0, 10 - (b - a - 1)).\n\nThe single official score is:\n\nscore = min(1, 142 / (C + 1))\n\nA feasible timetable with C <= 141 receives 1.0. A feasible timetable with C > 141 receives partial credit. Global optimality is not required or claimed.\n\nThe private reference has zero hard errors and C = 141. The reference package also includes a distinct feasible alternative fixture with C = 141, a feasible C = 142 calibration fixture scoring 142/143, and an invalid missing-game fixture scoring 0. These fixtures check full-credit, partial-credit and invalid-output behavior, including acceptance of a timetable that differs from the reference. They are examples used to validate the evaluator, not an exhaustive list of acceptable answers.\n\nDiagnostic fields explain the official result and are not additional scores. Evaluator or infrastructure failures must be investigated separately rather than counted as agent failure.\n\nReviewer-facing provenance and public-answer reuse checks\n\nThe construction materials in the private reference package identify the QOBLIB Addition_032_NoSoft template and the public schedule used as a CP-SAT construction hint. A new witness timetable was generated, and compatible restrictions were subsequently sampled. The specific restrictions were not independently collected from an operating league. This is a synthetic exercise using professional scheduling constraint families, not a historical or commissioned league season.\n\nA deterministic recheck of the unchanged files confirmed:\n\n* The final instance contains 246 constraint entries; 243 differ in attributes from the positionally corresponding upstream entries.\n* The final reference contains 197 game triples absent from the public hint.\n* Submitting the unmodified public hint against the final instance produces 52 hard-constraint error entries and scores 0.\n* The private reference has zero hard errors and continues to score 1.0 with C = 141.\n\nEight bounded transformations of the public hint were also checked. For each round transformation below, the first count preserves home/away assignments and the second exchanges home and away:\n\n* Identity: 52 and 109 hard-constraint error entries.\n* Full round reversal: 86 and 83 hard-constraint error entries.\n* Half-season exchange: 95 and 78 hard-constraint error entries.\n* Reversal within each half: 81 and 80 hard-constraint error entries.\n\nAll eight transformed schedules score 0. These counts refer to diagnostic error entries, not separate scores or necessarily the number of individual violation units.\n\nThe eight transformation results are reported recheck results. A standalone script and individual raw outputs for those eight checks are not included in the original archives. The archives contain the evaluator, source schedule and final instance needed to reproduce them.\n\nA separate retained historical record, construction/public_solution_reuse_check.json, lists 51 direct-reuse checks, including 25 schedules with the required 240 games; all 51 were recorded as invalid. Those 51 checks were not rerun as part of this recheck.\n\nThese are bounded checks against direct reuse. They do not prove non-isomorphism, absence of memorization, resistance to arbitrary relabeling or solution repair, or operational representativeness. Construction code and retained records are supplied for inspection, with historical logging limitations disclosed in REVIEW_NOTES.md. Public provenance and synthetic status remain explicitly disclosed.\n\nModel self-test evidence and frozen-task consistency\n\nThe input, reference, evaluator and scoring rule remain the same frozen versions used for both documented model attempts: GPT-6 Astra (High) and GPT-5.6 Sol (Extra High), run through Codex.\n\nThe evidence distinguishes Astra’s normally completed submission from Sol’s frozen deadline candidate. Both evaluated schedules received 0.0 because they violated mandatory constraints. Sol’s deadline candidate was evaluated as preserved at cutoff; its score was not assigned merely because the run reached its time limit, and it is not presented as a normally completed final delivery.\n\nThe evidence package reports the two attempts separately, including their run conditions, frozen candidate files and evaluation results. These observations describe performance in the documented attempts; they do not establish a population success rate or prove that other attempts, models or methods cannot solve the task.","software_and_version":"Python 3.12.14 (standard-library evaluator); optional optimization tools such as OR-Tools CP-SAT or HiGHS. No proprietary solver is required.","specific_requirements":null,"expected_completion_time":null},"files":[{"file_id":"173dafbd-4598-49ee-bde6-319b42e798e6","filename":"league_scheduling_input_materials.zip","category":"input_materials","content_type":"application/zip","size_bytes":19732},{"file_id":"4da14121-186e-48ae-b37c-82830148d27c","filename":"league_scheduling_reference_and_evaluation.zip","category":"reference_output","content_type":"application/zip","size_bytes":1348065},{"file_id":"56496a9f-4944-4a4e-95aa-413a6e02a153","filename":"league_scheduling_difficulty_evidence.zip","category":"difficulty_self_test_evidence","content_type":"application/zip","size_bytes":590480}],"deep_review":{"overall_verdict":"Accept","review_text":"**Overall Verdict:** Accept — The submitted revision is complete, internally consistent, objectively verifiable, and usable as a synthetic sports-scheduling task.\n\n**Completeness Check:**\n- Instruction: Complete — Clear deliverable, constraints, and acceptance conditions.\n- Inputs: Complete — The input package provides the instance, task specification, evaluator, score target, tools note, and licenses.\n- Toolchain: Complete — Python standard library scoring is documented; optional solvers are freely obtainable.\n- Reference output: Complete — A protected feasible reference and calibration fixtures were independently checked against the stated rules.\n- Rubric: Complete — The feasibility gate, partial-credit formula, and full-credit threshold are explicit.\n\n**File and Task Reachability:**\nAttachment classification: reachable. Task classification: reachable. All three manifest-listed ZIP attachments were downloaded in full, matched their declared sizes, passed archive integrity checks, and contained no encrypted, traversal, link, device, or executable-binary members. I inspected the canonical input files, reference schedules, scoring configuration, provenance and licensing records, fixture checks, and both model-run records. Root package manifests verified all 247 reference-package and 231 difficulty-package covered files; JSON and JSONL records parsed successfully. The primary XML instance was parsed and contains 16 teams, 30 rounds, and 246 hard constraints. The historical compressed LP source files were inventory- and manifest-checked but not semantically decompressed due to unavailable XZ tooling; they are non-critical construction evidence.\n\nIndependent static validation confirmed the reference and alternative schedules are feasible with soft penalty 141, the partial fixture is feasible with penalty 142, and the missing-game fixture fails mandatory conditions. The solver-visible path is complete: use the eight input files to produce `schedule.json`, then score it with the trusted frozen evaluator. 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:**\npublic_benchmark — The evidence affirmatively identifies QOBLIB/ITC2021 as the public structural source and includes upstream materials. The submitted instance documents substantial constraint resampling and a distinct reference schedule, with retained checks showing direct public-hint reuse is infeasible. Public provenance was not independently searched in this review environment; solver access must continue to exclude the reference, construction, and difficulty-evidence packages.\n\n**Recommended Changes:**\nThe submission provides a well-defined synthetic optimization workflow, strong fixture coverage, and a deterministic grader. No changes are required.","reviewed_at":"2026-09-19T07:26:52.049469Z"},"claim":{"id":"a982bd7e-2060-4760-8918-e2885da626d2","submission_id":"167fb43c-078e-4b24-a766-ef24def939c8","submission_revision_id":"f91e187d-e717-455e-b611-b82111e3f19a","builder":"builder-01","status":"active","claimed_at":"2026-10-15T15:29:34.765538Z","delivered_at":null,"ended_at":null,"delivery_note":null,"end_reason":null}},"revision_is_current":true}