{ "meta_info": { "case_id": "case41_02", "bench_subset": "NeuroBench-Sleep", "difficult": 1.5, "original_dataset": "ISRUC" }, "agent_input": { "data_path": "data/sleep/ISRUC_02.edf", "label_path": "data/sleep/ISRUC_02.npy", "instruction": "Use the sleep file and paired labels to calculate sleep mean SpO2, wake mean SpO2, and sleep minimum SpO2. Convert SaO2 to 1 Hz by per-second median; accept 50-100%, remove isolated <=2-second outliers more than 4 points from a centered 9-second median, interpolate only bounded internal gaps <=30 seconds, apply a centered 9-second median, and exclude all remaining missing seconds. Treat N1/N2/N3/R as sleep and W as wake. Report percentages. ISRUC: SaO2=oxygen saturation; X5=snore; X6/DC3=airflow; X7/X8=abdominal effort." }, "eval_config": { "parser_prompt": "### ROLE\nYou are a precise JSON Extraction Engine for sleep medicine reports.\n\n### TASK\nExtract sleep mean SpO2, wake mean SpO2, and sleep minimum SpO2.\n\n### STRICT CONSTRAINTS (MANDATORY)\n1. Output ONLY a valid JSON object.\n2. Do not include Markdown, explanations, units, or extra fields.\n3. Keys must be EXACTLY \"sleep_mean_spo2\", \"wake_mean_spo2\", and \"sleep_min_spo2\".\n4. Values must be FLOAT values or null.\n5. Return null for a missing or unclear value.\n\n### OUTPUT TEMPLATE\n{\"sleep_mean_spo2\": , \"wake_mean_spo2\": , \"sleep_min_spo2\": }", "metrics": [ { "metric_id": "sleep_mean_oxygen_saturation_accuracy", "type": "numeric_check", "target_key": "sleep_mean_spo2", "weight": 33, "params": { "gt_value": 96.35141244472393, "tolerance": 4.817570622236197 } }, { "metric_id": "wake_mean_oxygen_saturation_accuracy", "type": "numeric_check", "target_key": "wake_mean_spo2", "weight": 33, "params": { "gt_value": 96.3768491908515, "tolerance": 4.818842459542576 } }, { "metric_id": "sleep_min_oxygen_saturation_accuracy", "type": "numeric_check", "target_key": "sleep_min_spo2", "weight": 34, "params": { "gt_value": 90.3370649259306, "tolerance": 4.51685324629653 } } ] } }