{ "meta_info": { "case_id": "case08_06", "bench_subset": "NeuroBench-Multi", "difficult": 1, "original_dataset": "DEAP" }, "agent_input": { "data_path": "data/multi/DEAP_01.bdf", "instruction": "From Respiration channel `Resp`, analyze the half-open interval `[60, 120)` seconds at its native sampling rate.\n\nApply the declared fourth-order 0.05–1 Hz band-pass filter.\nRobust-z-score the filtered signal to obtain the normalized signal.\nDetect peaks using a minimum distance of 1024 samples and prominence 0.5.\nSet `feature_value` to the mean peak-to-preceding-trough amplitude of the normalized signal." }, "eval_config": { "parser_prompt": "### ROLE\nYou are a precise JSON Extraction Engine for neurophysiological data. Your sole task is to convert natural language reports into structured JSON data.\n\n### TASK\nExtract the final scalar feature produced by the complete declared signal-analysis procedure.\nApply the declared fourth-order 0.05–1 Hz band-pass filter to channel `Resp` over `[60, 120)`, robust-z-score the filtered signal, and detect peaks with a minimum distance of 1024 samples and prominence 0.5. Report the final requested scalar: the mean peak-to-preceding-trough amplitude.\nExtract the final requested aggregate only, not intermediate filtered, tonic, phasic, normalized, peak, or smoothed values.\n\n### STRICT CONSTRAINTS (MANDATORY)\n1. Output ONLY a valid JSON object.\n2. DO NOT include Markdown code blocks.\n3. DO NOT include conversational text, explanations, or units.\n4. The JSON key must be EXACTLY `feature_value`.\n5. The value must be one finite numeric scalar; integer counts are allowed when the requested feature is a count.\n6. If the final feature value is missing or cannot be identified, return {\"feature_value\": null}.\n\n### OUTPUT TEMPLATE\n{\"feature_value\": }", "metrics": [ { "metric_id": "feature_value_accuracy", "type": "numeric_check", "target_key": "feature_value", "weight": 100.0, "params": { "gt_value": 2.359312025004674, "tolerance": 0.2359312025004674 } } ] } }