| {
|
| "meta_info": {
|
| "case_id": "MentalArithmetic_01.edf",
|
| "bench_subset": "NeuroBench-Core",
|
| "difficult": 1.5,
|
| "original_dataset": "MentalArithmetic"
|
| },
|
| "agent_input": {
|
| "data_path": "data/core/MentalArithmetic_01.edf",
|
| "instruction": "Please select the specified central EEG channel C3, compute the 49-51Hz narrowband power before notch filtering, apply a 50Hz FIR notch filter, compute the 49-51Hz narrowband power after notch filtering, calculate the ratio post_notch_power / pre_notch_power, and report both the ratio and whether line-noise interference was successfully suppressed. Define successful suppression as a ratio strictly below 0.5."
|
| },
|
| "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 two outputs from the agent report:\n1) suppression ratio defined as post_notch_power / pre_notch_power\n2) whether line-noise interference was successfully suppressed\n\n### STRICT CONSTRAINTS (MANDATORY)\n1. Output ONLY a valid JSON object.\n2. DO NOT include Markdown code blocks.\n3. DO NOT include any conversational text or explanations.\n4. Keys in JSON must be EXACTLY \"suppression_ratio\" and \"suppressed\".\n5. \"suppression_ratio\" must be a FLOAT or null.\n6. \"suppressed\" must be either true, false, or null.\n\n### OUTPUT TEMPLATE\n{\"suppression_ratio\": <float|null>, \"suppressed\": <bool|null>}",
|
| "metrics": [
|
| {
|
| "metric_id": "suppression_ratio_accuracy",
|
| "type": "numeric_check",
|
| "target_key": "suppression_ratio",
|
| "weight": 70,
|
| "params": {
|
| "gt_value": 0.7462343178213074,
|
| "tolerance": 0.07462343178213075
|
| }
|
| },
|
| {
|
| "metric_id": "suppression_success_accuracy",
|
| "type": "categorical_check",
|
| "target_key": "suppressed",
|
| "weight": 30,
|
| "params": {
|
| "gt_value": false
|
| }
|
| }
|
| ]
|
| }
|
| }
|
|
|
