{"submission_id":"e0594b3d-9699-4ea8-8a61-33be4be97765","submission_revision_id":"c937efe7-ea33-419e-8eec-598967cd34ce","revision_version":3,"submission_status":"submitted","submitted_at":"2026-08-18T17:05:48.602401Z","submitter_name":"Dongrong Yang","submitter_email":"hlthrevolution21@gmail.com","task":{"status":"submitted","version":3,"extra_fields":{"difficulty_self_test":{"model":"gpt-5.6-terra (second tier; max reasoning)","harness":"Codex CLI 0.147.0-alpha.1.2; isolated offline workspace-write harness; 5,400 s limit","estimated_score":"<1%"}},"submitted_at":"2026-08-18T17:05:48.602401+00:00","industry_domain":"Medical Physics — HDR Brachytherapy","task_short_name":"tg43_hdr_dwell_optimization_1","operating_system":"Linux","task_description":"Objective:\nAct as a medical physicist producing a robust single-fraction HDR Ir-192 dwell-time plan for a synthetic prostate-like phantom with a focal boost. This benchmark is for research/evaluation only, not clinical use.\n\nStarting state:\n- source_model.csv: a fixed 464-row along-away table extracted directly from the public CLRP TG-43 v2 AAPM/ESTRO WG-MBDCA generic HDR Ir-192 workbook.\n- dwell_positions.csv: 130 candidate positions across ten fixed catheters.\n- structure_points.csv: 3,340 nominal points for CTV, BOOST, URETHRA, RECTUM, BLADDER, and RING.\n- uncertainty_model.json: analytic geometry and six declared anatomy/source-position scenarios.\n- prescription.json: source strength, prescriptions, structure volumes, dose-volume limits, and delivery constraints.\n\nInstructions:\n1. Reconstruct dose with along=point_z-dwell_z and away=hypot(point_x-dwell_x,point_y-dwell_y); convert rate*S_k*t/3600/100 to Gy.\n2. Discard away=0, natural-log positive rates, bilinearly interpolate the along/away grid, exponentiate, and clip to table bounds.\n3. Account for all six scenarios, including anatomy changes and scenario-specific catheter shifts. Do not overfit visible points.\n4. Simultaneously satisfy every worst-case target, boost, OAR, ring, and delivery gate.\n5. Use finite non-negative 0.1-second dwell times, each <=10 s, adjacent differences <=2 s, total <=300 s, and <=10 active catheters.\n6. Internet access is disabled. Time limit: 5,400 seconds.\n\nRequired outputs:\n- dwell_times.csv: exactly 130 unique rows with dwell_id, catheter_id, dwell_time_s and unchanged identities.\n- report.md: interpolation, dose calculation, uncertainty handling, robust optimization, delivery handling, and trade-offs.\n\nNo synthetic defects are injected or scored. Scoring is all-or-nothing.","software_licensing":"Free/Open Source","evaluation_criteria":null,"verification_method":"The evaluator validates exactly 130 unique dwell rows, required columns, unchanged dwell IDs/catheter assignments, and finite numeric times. It ignores submitted dose claims and reconstructs dose from the supplied fixed public CLRP source model using the stated positive-away natural-log bilinear interpolation.\n\nDose is evaluated on 16,980 independent hidden points in all six declared scenarios. Every worst-case gate is mandatory:\n- CTV D90 >=6.9 Gy; V100 >=88.5%; D98 >=5.8 Gy; V150 <=35%.\n- BOOST D90 >=8.9 Gy; V100 >=87%; D98 >=8.0 Gy.\n- URETHRA D10 <=8.7 Gy; maximum <=9.5 Gy.\n- RECTUM D2cc <=6.2 Gy; BLADDER D2cc <=6.65 Gy; RING D2cc <=9.5 Gy.\n- Delivery: non-negative; exact 0.1-second quantization; each dwell <=10 s; adjacent difference <=2 s; total <=300 s; <=10 active catheters.\n\nThere are 18 binary gates: 12 dosimetric and 6 delivery-validity gates. Official score is 1 only if all 18 pass; otherwise 0. Diagnostic gate fraction is not partial credit.\n\nThe oracle passes 18/18: CTV D90=6.907 Gy, V100=89.00%, D98=5.982 Gy, V150=32.25%; BOOST D90=8.932 Gy, V100=87.22%, D98=8.630 Gy; urethra D10=8.615 Gy; rectum=6.011 Gy; bladder=6.602 Gy; ring=9.125 Gy; total=241.7 s. Seven regression tests reject missing outputs, duplicate rows, changed catheter assignments, negative/unquantized times, and malformed values.\n\nMajor-revision response: the previous deliberately corrupted source branch, protected values, defect map, repair output, and repair gates are completely removed. The source table is a fixed direct input and no defects are injected, hidden, repaired, or scored.","software_and_version":"Python 3.11; NumPy 1.26.4; pandas 2.2.2; SciPy 1.13.0","specific_requirements":null,"expected_completion_time":null},"files":[{"file_id":"8b34beb2-33a5-4fb4-befb-b19a739f6a6c","filename":"tg43-hdr-reference-evaluation.zip","category":"reference_output","content_type":"application/zip","size_bytes":407881},{"file_id":"981cae56-441f-4ed6-ad66-3641c433cbb5","filename":"terra_planning_only_score.json","category":"difficulty_self_test_evidence","content_type":"application/json","size_bytes":4396},{"file_id":"97c076dd-87fc-4716-98ed-00b8e168cc68","filename":"tg43-hdr-input-materials.zip","category":"input_materials","content_type":"application/zip","size_bytes":69727}],"deep_review":{"overall_verdict":"Strong Accept","review_text":"**Overall Verdict:** Strong Accept — The submission is complete, internally coherent, independently verifiable, professionally representative, and reachable end to end.\n\n**Completeness Check:**\n- Instruction: Complete — Clearly defines dose reconstruction, interpolation, six uncertainty scenarios, delivery constraints, outputs, runtime, and all-or-nothing scoring.\n- Inputs: Complete — All stated files, schemas, row counts, units, identities, and analytic geometries are present and consistent; the only four blank source rates occur in the explicitly discarded away-zero column.\n- Toolchain: Complete — Specifies compatible open-source Python, NumPy, pandas, and SciPy versions with a suitable Linux container definition and single-machine resource profile.\n- Reference output: Complete — Includes a valid 130-row quantized dwell plan, methodology report, hidden evaluation points, passing reference score, evaluator, tests, and provenance materials.\n- Rubric: Complete — Defines twelve dosimetric and six delivery gates, strict thresholds, structural validation, deterministic hidden-scenario evaluation, binary scoring, and diagnostic failure reporting.\n\n**File and Task Reachability:**\nThe attachment set is `reachable`, and the end-to-end task is `reachable`. I inspected `tg43-hdr-input-materials.zip`, including its instruction, README, task card, environment definition, source model, dwell positions, visible structure points, prescription, and uncertainty model; `tg43-hdr-reference-evaluation.zip`, including the oracle outputs, hidden points, score, evaluator, generator, calibration and solution materials, tests, documentation, and source workbook; and `terra_planning_only_score.json`. All archive members were inspected, with no unreviewed content, encryption, unsafe paths, links, devices, macros, or excessive expansion. The workbook is a valid macro-free XLSX, its supplied checksum is internally consistent, and all 464 exported source rows match its AlongAway worksheet exactly.\n\nThe review host lacked the declared Python runtime, so the submitted Python scripts and tests were not executed. This is a reviewer-tooling limitation, not a submission defect. An independent read-only reconstruction reproduced all six scenario results and aggregate reference metrics to numerical precision and confirmed that all 18 gates pass. The completion path is clear: reconstruct dwell-to-point dose from the supplied grid, sample or otherwise robustly model the declared analytic scenarios, optimize and quantize 130 dwell times, produce the CSV and report, and undergo evaluator-owned identity, delivery, and hidden dosimetry checks. The claimed public provenance could not be externally searched within the evidence boundary, but the workbook’s internal labeling, cited source description, supplied checksum, and exact extraction consistency provide strong internal support. 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 revision successfully removes the prior defect-repair branch and presents a focused robust inverse-planning task with strong evaluator separation and independently confirmed reference behavior. No changes are required.","reviewed_at":"2026-08-18T17:17:06.598556Z"},"claim":null}