| { |
| "meta_info": { |
| "case_id": "Physionet2018_02.edf", |
| "bench_subset": "NeuroBench-Sleep", |
| "difficult": 2, |
| "original_dataset": "Physionet2018" |
| }, |
| "agent_input": { |
| "data_path": "data/sleep/Physionet2018_02.edf", |
| "instruction": "Given the sleep file, determine whether a respiratory-effort-related arousal (RERA) event is present in each of the following five 60-second sleep segments: A: 320.3-321.3 minutes; B: 251.74-252.74 minutes; C: 291.5-292.5 minutes; D: 305.98-306.98 minutes; E: 367.31-368.31 minutes. Report yes or no for segments A-E in order. Distinguish RERA from apnea, hypopnea, and segments without a target respiratory event. Respiratory channels for Physionet2018: ABD = abdominal respiratory effort; CHEST = thoracic respiratory effort; AIRFLOW = airflow; SaO2 = oximetry." |
| }, |
| "eval_config": { |
| "parser_prompt": "### ROLE\nYou are a precise JSON Extraction Engine for sleep medicine reports.\n\n### TASK\nExtract whether RERA is present in segments A, B, C, D, and E.\n\n### STRICT CONSTRAINTS (MANDATORY)\n1. Output ONLY a valid JSON object.\n2. Do not include Markdown, explanations, or extra fields.\n3. The keys must be EXACTLY \"A\", \"B\", \"C\", \"D\", and \"E\".\n4. Each value must be exactly \"yes\", \"no\", or null.\n5. Normalize affirmative RERA conclusions to \"yes\" and absent/no-RERA conclusions to \"no\".\n6. If a segment is missing or unclear, return null for that segment.\n\n### OUTPUT TEMPLATE\n{\"A\":\"yes\",\"B\":\"no\",\"C\":\"no\",\"D\":\"yes\",\"E\":\"no\"}", |
| "metrics": [ |
| { |
| "metric_id": "segment_A_rera_accuracy", |
| "type": "categorical_check", |
| "target_key": "A", |
| "weight": 17, |
| "params": { |
| "gt_value": "no" |
| } |
| }, |
| { |
| "metric_id": "segment_B_rera_accuracy", |
| "type": "categorical_check", |
| "target_key": "B", |
| "weight": 17, |
| "params": { |
| "gt_value": "no" |
| } |
| }, |
| { |
| "metric_id": "segment_C_rera_accuracy", |
| "type": "categorical_check", |
| "target_key": "C", |
| "weight": 16, |
| "params": { |
| "gt_value": "no" |
| } |
| }, |
| { |
| "metric_id": "segment_D_rera_accuracy", |
| "type": "categorical_check", |
| "target_key": "D", |
| "weight": 25, |
| "params": { |
| "gt_value": "yes" |
| } |
| }, |
| { |
| "metric_id": "segment_E_rera_accuracy", |
| "type": "categorical_check", |
| "target_key": "E", |
| "weight": 25, |
| "params": { |
| "gt_value": "yes" |
| } |
| } |
| ] |
| } |
| } |
