{
  "rejected_claims": [
    {
      "filename": "clinical-llm-evaluation-uses-medical-exam-questions-not-real-patient-data-creating-systematic-benchmark-validity-gap.md",
      "issues": [
        "missing_attribution_extractor"
      ]
    },
    {
      "filename": "conversational-clinical-ai-shows-19-point-accuracy-drop-versus-single-turn-questions-revealing-interaction-complexity-gap.md",
      "issues": [
        "missing_attribution_extractor"
      ]
    }
  ],
  "validation_stats": {
    "total": 2,
    "kept": 0,
    "fixed": 2,
    "rejected": 2,
    "fixes_applied": [
      "clinical-llm-evaluation-uses-medical-exam-questions-not-real-patient-data-creating-systematic-benchmark-validity-gap.md:set_created:2026-03-24",
      "conversational-clinical-ai-shows-19-point-accuracy-drop-versus-single-turn-questions-revealing-interaction-complexity-gap.md:set_created:2026-03-24"
    ],
    "rejections": [
      "clinical-llm-evaluation-uses-medical-exam-questions-not-real-patient-data-creating-systematic-benchmark-validity-gap.md:missing_attribution_extractor",
      "conversational-clinical-ai-shows-19-point-accuracy-drop-versus-single-turn-questions-revealing-interaction-complexity-gap.md:missing_attribution_extractor"
    ]
  },
  "model": "anthropic/claude-sonnet-4.5",
  "date": "2026-03-24"
}