{
  "annotation_id": "59e6543b-65df-416f-ae80-55172a6cb073",
  "date_created": "2026-02-17T05:53:16.129000Z",
  "date_modified": "2026-02-17T05:53:16.129000Z",
  "file_hash": "636f9b68a6d6991819e9e6b07b8bf25c4f252b895e40a7b63f725efba374455b",
  "private": false,
  "record": {
    "abstract": "Conversational AI is starting to support real clinical work, but most evaluation methods miss how compliance depends on the full course of a conversation. We introduce Obligatory-Information Phase Structured Compliance Evaluation (OIP-SCE), an evaluation method that checks whether every required clinical obligation is met, in the right order, with clear evidence for clinicians to review. This makes complex rules practical and auditable, helping close the gap between technical progress and what healthcare actually needs. We demonstrate the method in two case studies (respiratory history, benefits verification) and show how phase-level evidence turns policy into shared, actionable steps. By giving clinicians control over what to check and engineers a clear specification to implement, OIP-SCE provides a single, auditable evaluation surface that aligns AI capability with clinical workflow and supports routine, safe use.",
    "arxiv_id": "2601.08690",
    "authors": [
      "Shubham Kulkarni",
      "Alexander Lyzhov",
      "Shiva Chaitanya",
      "Preetam Joshi"
    ],
    "categories": [
      "cs.AI"
    ],
    "license": "http://creativecommons.org/licenses/by/4.0/",
    "title": "All Required, In Order: Phase-Level Evaluation for AI-Human Dialogue in Healthcare and Beyond",
    "url": "https://arxiv.org/abs/2601.08690",
    "version": "v1"
  },
  "schema_id": "dorsal/arxiv",
  "source": {
    "execution_id": "074cfe22-531b-49d8-bb19-e90e08a70383",
    "id": "arXiv Dataset",
    "type": "Model",
    "variant": "snapshot-2026-01-17",
    "version": "0.1.0"
  },
  "user_id": 1000002
}