{"claim":{"id":"1e8ddccb-5938-4038-8f5f-df3d92b325b2","submission_id":"27c61806-3648-4355-abdf-70cd929b5961","submission_revision_id":"ec22417c-94e1-45d8-8612-56770f598742","builder":"builder-01","status":"active","claimed_at":"2026-10-15T15:04:00.232430Z","delivered_at":null,"ended_at":null,"delivery_note":null,"end_reason":null},"task":{"submission_id":"27c61806-3648-4355-abdf-70cd929b5961","submission_revision_id":"ec22417c-94e1-45d8-8612-56770f598742","revision_version":7,"submission_status":"under_review","submitted_at":"2026-08-15T23:15:40.713266Z","submitter_name":"Yongshuo Zong","submitter_email":"yongshuo.zong@gmail.com","task":{"status":"submitted","version":7,"extra_fields":{"difficulty_self_test":{"model":"Gemini Flash 3.6","estimated_score":"20–40%"}},"submitted_at":"2026-08-15T23:15:40.713266+00:00","industry_domain":"Clinical Diagnostic","task_short_name":"icd_coding_instance_1","operating_system":"Linux","task_description":"Objective: Assign all applicable ICD-10-CM diagnosis codes and ICD-10-PCS procedure codes for a complex inpatient hospital admission.\n\nStarting State: A discharge summary (input/discharge_summary.txt) for a 67-year-old male admitted with acute cholangitis. The patient has a multi-system medical history buried across the medication list, physical exam, and lab results. The working directory also contains the complete FY2025 ICD-10-CM codebook (~74,000 diagnosis codes in input/icd10cm_codebook.txt), the FY2025 ICD-10-PCS codebook (~79,000 procedure codes in input/icd10pcs_codebook.txt), patient demographics (input/patient_demographics.json), and a task prompt (task_prompt.txt). An empty output folder (output/) is provided. Python 3 with standard libraries is available.\n\nInstructions & Rules: Read the discharge summary and identify the principal diagnosis and all reportable secondary diagnoses — defined as conditions that coexist at admission or develop during the stay AND that affect patient care (requiring clinical evaluation, therapeutic treatment, diagnostic procedures, extended length of stay, or increased nursing care). Identify all significant procedures — defined as therapeutic and diagnostic procedures that carry procedural risk, require specialized training, or are surgical in nature, including endoscopic procedures, biopsies, blood transfusions, and intraoperative imaging (e.g., fluoroscopy during ERCP). Search the ICD-10-CM and ICD-10-PCS codebooks to find the most specific code for each condition and procedure. Determine the principal diagnosis (the condition established after study to be chiefly responsible for the admission, sequenced as seq=1). Write the output as a JSON file to output/coding_output.json following the schema specified in task_prompt.txt. Do not invent codes — every code must exist in the provided codebooks. Code to the highest level of specificity supported by the documentation; do not assign a more specific code than what the medical record explicitly states.","software_licensing":"Free/Open Source","evaluation_criteria":null,"verification_method":"Compare the agent's output/coding_output.json against reference/reference_coding.json using the evaluation script software/main.py. Scoring is a weighted combination of three components. Evaluation is based on ICD code matching only — descriptions and sequencing order are recorded but not scored.\n\nPrincipal Diagnosis Match (30% weight): The agent's principal diagnosis ICD-10-CM code must exactly match the reference code (after normalizing by stripping dots and uppercasing). Score: 1.0 if exact match, 0.0 otherwise.\n\nSecondary Diagnoses Set-F1 (40% weight): Compute set-level F1 between the agent's secondary diagnosis codes and the reference secondary diagnosis codes. F1 = 2 × Precision × Recall / (Precision + Recall), where Precision = |predicted ∩ reference| / |predicted| and Recall = |predicted ∩ reference| / |reference|. All codes are normalized (strip dots, uppercase) before comparison. This case has 21 secondary diagnosis codes and 6 procedure codes in the reference.\n\nProcedures Set-F1 (30% weight): Same set-level F1 metric applied to ICD-10-PCS procedure codes.\n\nFinal Score = 0.30 × (principal_dx_match) + 0.40 × (secondary_dx_f1) + 0.30 × (procedure_f1)\n\nA perfect score is 1.0. The score is deterministic and fully automated.","software_and_version":"Python 3.12","specific_requirements":null,"expected_completion_time":null},"files":[{"file_id":"527e21a5-4f1e-4d3a-9f54-16a9e803a155","filename":"icd_coding_instance_1_input.zip","category":"input_materials","content_type":"application/zip","size_bytes":2180253},{"file_id":"53ec2e57-b4d7-46e4-8fc0-744ffd71d6e5","filename":"reference_coding.json","category":"reference_output","content_type":"application/json","size_bytes":3794}],"deep_review":{"overall_verdict":"Strong Accept","review_text":"**Overall Verdict:** Strong Accept — The submission is complete, internally consistent, professionally representative, objectively scorable, and reachable end to end without material risk.\n\n**Completeness Check:**\n- Instruction: Complete — Clearly defines the coding objective, reportability criteria, significant procedures, sequencing rules, code specificity, and exact JSON output schema.\n- Inputs: Complete — The clinical summary and demographics are readable, and the FY2025 codebooks contain the stated 74,260 diagnosis codes and 78,948 procedure codes with valid, unique records.\n- Toolchain: Complete — Python 3.12 and standard libraries are legally obtainable and sufficient; the supplied evaluator uses only standard-library functionality.\n- Reference output: Complete — Valid JSON contains one principal diagnosis, 21 unique secondary diagnoses, and six unique procedures. Every reference code exists in the supplied codebooks and is supported by documented clinical evidence.\n- Rubric: Complete — Deterministic exact-match and set-F1 scoring provides clear partial credit with explicit weights and normalization. The intentional code-only scoring scope is disclosed.\n\n**File and Task Reachability:**\nThe attachment set is `reachable`, and the end-to-end task is `reachable`. The inspected attachments were `icd_coding_instance_1_input.zip` and `reference_coding.json`. Within the ZIP, `task_prompt.txt`, `discharge_summary.txt`, `patient_demographics.json`, both ICD-10 codebooks, and the evaluator source were inspected. The archive is readable, unencrypted, free of unsafe paths or links, and expands to a reasonable size. Duplicate core input entries are byte-identical and do not impede use; macOS metadata was inventoried but not decoded because it has no task role. No task-relevant content remained unreviewed. The evaluator was inspected statically rather than executed because Python was unavailable in the review environment; this is a reviewer-tooling limitation, not a submission defect. A solver can read the clinical evidence and codebooks, write `output/coding_output.json`, and be evaluated against the separately held reference using the supplied deterministic evaluator. The protected answer is not present in the solver-visible input bundle. 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 is ready and requires no material changes. Removing duplicate archive entries and macOS metadata would be optional packaging cleanup only.","reviewed_at":"2026-08-15T23:20:05.888087Z"},"claim":{"id":"1e8ddccb-5938-4038-8f5f-df3d92b325b2","submission_id":"27c61806-3648-4355-abdf-70cd929b5961","submission_revision_id":"ec22417c-94e1-45d8-8612-56770f598742","builder":"builder-01","status":"active","claimed_at":"2026-10-15T15:04:00.232430Z","delivered_at":null,"ended_at":null,"delivery_note":null,"end_reason":null}},"revision_is_current":true}