Datasets:
| { | |
| "meta_info": { | |
| "case_id": "case39_40", | |
| "bench_subset": "NeuroBench-Multi", | |
| "difficult": 1, | |
| "original_dataset": "Multi_QA" | |
| }, | |
| "agent_input": { | |
| "data_path": [], | |
| "instruction": "Answer this standalone multimodal neurophysiology multiple-choice question: How should a fusion system treat one modality whose current signal quality is poor? Options: A: A mechanical majority vote is used without checking modality reliability. B: A quality-aware rule reduces the contribution of evidence from the unreliable modality. C: Every modality retains an identical fixed weight regardless of quality. D: The unreliable modality receives a larger weight because it is noisy. Select exactly one option, A, B, C, or D. Return only one JSON object with the single field answer and no explanation or extra fields." | |
| }, | |
| "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 answer choice from the agent's report.\n- answer: exactly one of A, B, C, or D.\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 extra fields.\n4. The JSON key must be EXACTLY \"answer\".\n5. The answer value must be exactly one of \"A\", \"B\", \"C\", or \"D\".\n6. If the answer is missing or unclear, return {\"answer\": null}.\n\n### OUTPUT TEMPLATE\n{\"answer\": \"<A | B | C | D or null>\"}", | |
| "metrics": [ | |
| { | |
| "metric_id": "knowledge_answer_accuracy", | |
| "type": "categorical_check", | |
| "target_key": "answer", | |
| "weight": 100, | |
| "params": { | |
| "gt_value": "B" | |
| } | |
| } | |
| ] | |
| } | |
| } | |