Datasets:
File size: 3,541 Bytes
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"meta_info": {
"case_id": "ISRUC_02.edf",
"bench_subset": "NeuroBench-Sleep",
"difficult": 1.5,
"original_dataset": "ISRUC"
},
"agent_input": {
"data_path": "data/sleep/ISRUC_02.edf",
"instruction": "Please analyze the EEG signals in the following three 5-minute windows of the provided sleep file: A: 64.0-69.0 minutes; B: 184.0-189.0 minutes; C: 354.5-359.5 minutes. Select EEG channels only. Determine which window is most slow-wave-rich, and report the delta-band relative power percentage for EEG channels in each of the three windows. Define delta relative power as power in 0.5-4Hz divided by total power in 0.5-40Hz, multiplied by 100. Report the selected window using only A, B, or C, and clearly state the delta relative power percentages for A, B, and C."
},
"eval_config": {
"parser_prompt": "### ROLE\nYou are a precise JSON Extraction Engine for sleep EEG analysis reports. Your sole task is to convert natural language reports into structured JSON data.\n\n### TASK\nExtract four final outputs from the agent's report:\n1) which one of windows A, B, and C is most slow-wave-rich\n2) the delta relative power percentage for window A\n3) the delta relative power percentage for window B\n4) the delta relative power percentage for window C\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 keys must be EXACTLY \"slow_wave_rich_window\", \"delta_ratio_A\", \"delta_ratio_B\", and \"delta_ratio_C\".\n5. \"slow_wave_rich_window\" must be exactly one of: \"A\", \"B\", \"C\", or null.\n6. Each delta ratio value must be a FLOAT percentage without a percent sign.\n7. If a report gives a fraction or proportion between 0 and 1, convert it to a percentage by multiplying by 100.\n8. If a value is missing or unclear, return null for that value.\n\n### OUTPUT TEMPLATE\n{\"slow_wave_rich_window\": <\"A\"|\"B\"|\"C\"|null>, \"delta_ratio_A\": <float|null>, \"delta_ratio_B\": <float|null>, \"delta_ratio_C\": <float|null>}",
"metrics": [
{
"metric_id": "slow_wave_rich_window_accuracy",
"type": "categorical_check",
"target_key": "slow_wave_rich_window",
"weight": 40,
"params": {
"gt_value": "B"
}
},
{
"metric_id": "delta_ratio_A_accuracy",
"type": "numeric_check",
"target_key": "delta_ratio_A",
"weight": 20,
"params": {
"gt_value": 19.16429604391837,
"tolerance": 0.9582148021959185
}
},
{
"metric_id": "delta_ratio_B_accuracy",
"type": "numeric_check",
"target_key": "delta_ratio_B",
"weight": 20,
"params": {
"gt_value": 83.8454977168564,
"tolerance": 4.19227488584282
}
},
{
"metric_id": "delta_ratio_C_accuracy",
"type": "numeric_check",
"target_key": "delta_ratio_C",
"weight": 20,
"params": {
"gt_value": 54.972775817497435,
"tolerance": 2.748638790874872
}
}
]
}
}
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