{
  "assess.predict": {
    "traces": [],
    "train": [],
    "demos": [],
    "signature": {
      "instructions": "Assess the clinical impact of transcription errors in medical conversations.\n\nCompare the ground truth conversation with the transcription conversation and determine\nif errors would affect patient care. Focus on THREE distinct severity levels.",
      "fields": [
        {
          "prefix": "Ground Truth Conversation:",
          "description": "${ground_truth_conversation}"
        },
        {
          "prefix": "Transcription Conversation:",
          "description": "${transcription_conversation}"
        },
        {
          "prefix": "Reasoning:",
          "description": "Brief clinical justification for the assessment."
        },
        {
          "prefix": "Clinical Impact:",
          "description": "Clinical impact class (return ONLY the number):\n        0 = No impact: cosmetic differences only (punctuation, capitalization, filler words)\n        1 = Minimal impact: some information missing/changed but NOT critical to diagnosis or treatment decisions  \n        2 = Significant impact: missing/incorrect information that COULD affect diagnosis, treatment, or patient safety\n        Return ONLY: 0, 1, or 2"
        }
      ]
    },
    "lm": {
      "model": "openrouter/google/gemini-2.5-pro",
      "model_type": "chat",
      "cache": true,
      "num_retries": 3,
      "finetuning_model": null,
      "launch_kwargs": {},
      "train_kwargs": {},
      "temperature": 0.1,
      "max_tokens": 8000
    }
  },
  "metadata": {
    "dependency_versions": {
      "python": "3.13",
      "dspy": "3.0.4",
      "cloudpickle": "3.1"
    }
  }
}