{
  "meta_info": {
    "case_id": "case08_09",
    "bench_subset": "NeuroBench-Multi",
    "difficult": 1,
    "original_dataset": "DEAP"
  },
  "agent_input": {
    "data_path": "data/multi/DEAP_04.bdf",
    "instruction": "From Temperature channel `Temp`, analyze the half-open interval `[0, 60)` seconds at its native sampling rate.\n\nUse the raw signal without an additional filter.\nSmooth it with a centered 2560-sample moving average with reflect padding.\nSet `feature_value` to the mean of the smoothed signal over the interval."
  },
  "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.\nUse channel `Temp` over `[0, 60)` without an additional filter. Apply a centered 2560-sample moving average with reflect padding and report the final requested scalar: the mean of the smoothed signal.\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\": <number|null>}",
    "metrics": [
      {
        "metric_id": "feature_value_accuracy",
        "type": "numeric_check",
        "target_key": "feature_value",
        "weight": 100.0,
        "params": {
          "gt_value": 32.658024,
          "tolerance": 3.2658024
        }
      }
    ]
  }
}