{
    "meta_info": {
        "case_id": "Mumtaz2016_03.edf",
        "bench_subset": "NeuroBench-Core",
        "difficult": 2.0,
        "original_dataset": "Mumtaz2016"
    },
    "agent_input": {
        "data_path": "data/core/Mumtaz2016_03.edf",
        "instruction": "Please select standard EEG channels, compute alpha power for each channel, and rank channels by alpha power in descending order. Output the top-5 channel names. Then determine the dominant brain region based on the number of top-5 channels in each region. If multiple regions tie for the highest count, output all tied regions. Use this region mapping: frontal=[Fp1-LE, F3-LE, F7-LE, Fz-LE, Fp2-LE, F4-LE, F8-LE]; central=[C3-LE, C4-LE, Cz-LE]; parietal=[P3-LE, P4-LE, Pz-LE, T5-LE, T6-LE]; occipital=[O1-LE, O2-LE]."
    },
    "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) top-5 channels ranked by alpha power\n2) dominant brain region or tied dominant brain regions\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 must be EXACTLY \"top5_alpha_power_channels\" and \"dominant_regions\".\n5. Extract the final top-5 ranked list, not a channel inventory or an intermediate table. top5_alpha_power_channels must contain exactly 5 strings or be null.\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 channel label must contain only uppercase A-Z letters and digits. Examples: O2-A1 -> O2; EEG Fp2-LE -> FP2; EEG T6 -> P8; Pz -> PZ. Preserve descending alpha-power order and do not sort alphabetically.\n10. For dominant_regions, lowercase the explicitly reported final dominant or tied regions and keep only exact values from: frontal, central, parietal, occipital. Ignore unsupported region labels and do not map or guess them.\n11. If the top-5 list is missing or does not contain exactly 5 identifiable labels, set top5_alpha_power_channels to null. If no supported dominant region is explicit, set dominant_regions to null.\n\n### OUTPUT TEMPLATE\n{\"top5_alpha_power_channels\": [\"CH1\", \"CH2\", \"CH3\", \"CH4\", \"CH5\"], \"dominant_regions\": [\"region\"]}",
        "metrics": [
            {
                "metric_id": "top5_alpha_power_sequence",
                "type": "sequence_match_check",
                "target_key": "top5_alpha_power_channels",
                "weight": 60,
                "params": {
                    "gt_value": [
                        "O2",
                        "O1",
                        "PZ",
                        "CZ",
                        "P8"
                    ],
                    "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
                }
            },
            {
                "metric_id": "dominant_region_set",
                "type": "set_match_check",
                "target_key": "dominant_regions",
                "weight": 40,
                "params": {
                    "gt_value": [
                        "parietal",
                        "occipital"
                    ],
                    "match_mode": "exact"
                }
            }
        ]
    }
}