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Normalize Foundational Analysis case ordering
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{
"meta_info": {
"case_id": "Mumtaz2016_01.edf",
"bench_subset": "NeuroBench-Core",
"difficult": 1.5,
"original_dataset": "Mumtaz2016"
},
"agent_input": {
"data_path": "data/core/Mumtaz2016_01.edf",
"instruction": "Please select only the real EEG channels from the raw signal (excluding non-EEG channels). Do not apply linear detrending. For each selected channel, obtain the power in the 0.1-0.5 Hz band and the total power in the 0.1-45 Hz band by integrating the PSD over frequency, then calculate the channel-wise baseline-drift power ratio. Average these channel-wise ratios to obtain the final ratio. Classify the baseline drift level as LOW, MEDIUM, or HIGH using these thresholds: LOW if ratio < 0.08, MEDIUM if 0.08 <= ratio < 0.25, and HIGH if ratio >= 0.25. Report both the final ratio value and the final level in your response."
},
"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 final outputs from the agent report:\n1) Baseline-drift power ratio (0.1-0.5 Hz / 0.1-45 Hz)\n2) Baseline-drift level\n\n### STRICT CONSTRAINTS (MANDATORY)\n1. Output ONLY a valid JSON object.\n2. DO NOT include Markdown code blocks (e.g., no backticks or json tags).\n3. DO NOT include any conversational text, explanations, or units.\n4. The keys in JSON must be EXACTLY \"drift_ratio\" and \"drift_level\".\n5. \"drift_ratio\" must be a FLOAT.\n6. \"drift_level\" must be one of \"LOW\", \"MEDIUM\", \"HIGH\".\n7. If one value is missing, return it as null.\n\n### OUTPUT TEMPLATE\n{\"drift_ratio\": <float|null>, \"drift_level\": <LOW|MEDIUM|HIGH|null>}",
"metrics": [
{
"metric_id": "baseline_drift_level_accuracy",
"type": "categorical_check",
"target_key": "drift_level",
"weight": 100,
"params": {
"gt_value": "LOW"
}
},
{
"metric_id": "baseline_drift_ratio_reference",
"type": "numeric_check",
"target_key": "drift_ratio",
"weight": 0,
"params": {
"gt_value": 0.032954,
"tolerance": 0.003295
}
}
]
}
}