{
    "meta_info": {
        "case_id": "BCIC2020-3_02.edf",
        "bench_subset": "NeuroBench-Core",
        "difficult": 1.5,
        "original_dataset": "BCIC2020-3"
    },
    "agent_input": {
        "data_path": "data/core/BCIC2020-3_02.edf",
        "instruction": "Please use the first 30 seconds of EEG channels, apply a 0.5-4Hz FIR bandpass filter, resample to 200Hz, compute channel-wise variance, and list the top five channel names ranked from highest to lowest variance."
    },
    "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 ranked top-5 EEG channel names by variance.\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. The key in JSON must be EXACTLY \"top5_channels\".\n5. Extract the final ranked list, not a channel inventory or an intermediate list. The value must be an array of exactly 5 strings.\n6. Normalize EACH reported channel independently: trim whitespace, remove one leading acquisition prefix EEG followed by a space, hyphen, or underscore, then uppercase the label.\n7. Remove one terminal reference suffix if present: -A1, -A2, -LE, -REF, -M1, -M2, or -AVG.\n8. Convert legacy aliases after removing the prefix and suffix: T3->T7, T4->T8, T5->P7, T6->P8.\n9. Each output label must contain only uppercase A-Z letters and digits. Examples: EEG Fp1-LE -> FP1; C3-A2 -> C3; EEG T4 -> T8; Fz -> FZ.\n10. Keep the five channels in the descending variance order reported. Do not sort the array alphabetically and do not substitute different channels.\n11. If the final list does not contain exactly 5 identifiable channel labels, return {\"top5_channels\": null}; do not guess.\n\n### OUTPUT TEMPLATE\n{\"top5_channels\": [\"CH1\", \"CH2\", \"CH3\", \"CH4\", \"CH5\"]}",
        "metrics": [
            {
                "metric_id": "variance_top5_channel_sequence",
                "type": "sequence_match_check",
                "target_key": "top5_channels",
                "weight": 100,
                "params": {
                    "gt_value": [
                        "FP2",
                        "AF7",
                        "F8",
                        "FP1",
                        "AF8"
                    ],
                    "match_mode": "weighted_partial_order",
                    "top_k": 5,
                    "position_weights": [
                        1.0,
                        0.8,
                        0.6,
                        0.4,
                        0.2
                    ],
                    "min_overlap": 3,
                    "allow_order_slip": 1
                }
            }
        ]
    }
}