sleep_assessment/cases/case13/case13_09.json

{
    "meta_info": {
        "case_id": "HMC_04.edf",
        "bench_subset": "NeuroBench-Sleep",
        "difficult": 1.5,
        "original_dataset": "HMC"
    },
    "agent_input": {
        "label_path": "data/sleep/HMC_04.npy",
        "instruction": "Please use the provided sleep-stage label file to calculate the Sleep Fragmentation Index (SFI). Define the sleep period as the interval from the first non-Wake epoch to the last non-Wake epoch. Within this sleep period, count the number of awakenings as the number of contiguous Wake (W) bouts, and count sleep-stage shifts as the number of adjacent epoch stage changes where both adjacent epochs are non-Wake sleep stages (N1, N2, N3, or R/REM). Calculate total sleep time as the number of non-Wake epochs multiplied by 30 seconds. SFI is defined as (number of awakenings + sleep-stage shifts) divided by total sleep time in hours, reported as events per hour of total sleep time. Please clearly report the final SFI value."
    },
    "eval_config": {
        "parser_prompt": "### ROLE\nYou are a precise JSON Extraction Engine for sleep medicine reports. Your sole task is to convert natural language reports into structured JSON data.\n\n### TASK\nExtract the Sleep Fragmentation Index (SFI) from the agent's report.\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 key must be EXACTLY \"sleep_fragmentation_index\".\n5. The value must be a FLOAT or null.\n6. If the value is missing or cannot be found, return {\"sleep_fragmentation_index\": null}.\n\n### OUTPUT TEMPLATE\n{\"sleep_fragmentation_index\": <float|null>}",
        "metrics": [
            {
                "metric_id": "sleep_fragmentation_index_accuracy",
                "type": "numeric_check",
                "target_key": "sleep_fragmentation_index",
                "weight": 100,
                "params": {
                    "gt_value": 13.461538461538462,
                    "tolerance": 0.6730769230769231
                }
            }
        ]
    }
}