Step 2: tool results

get_claim

{
  "include": [
    "arguments",
    "subclaims",
    "related",
    "findings",
    "dependents"
  ],
  "claim_id": "022b9cef-1397-4f4c-af7e-917df64bab6b"
}

{"claim":{"id":"022b9cef-1397-4f4c-af7e-917df64bab6b","kind":"claim","canonical_form":"Output-only monitoring reliably detects deliberate language-model underperformance only when intent is verbalized or rephrased responses conflict.","claim_type":"empirical_derived","state":"active","decomposition_status":"complete","importance":0.45,"contestation":null,"domains":[],"tags":[{"slug":"ai-sandbagging","name":"AI Sandbagging"},{"slug":"ai-control","name":"AI Control"}],"steward_state":"running","stewarded_at":"2026-11-14T06:38:06.373Z","canonical_direction_note":null,"created_at":"2026-11-13T21:47:42.900Z","updated_at":"2026-11-14T06:38:05.592Z","page_url":"https://minerval.ai/claims/022b9cef-1397-4f4c-af7e-917df64bab6b"},"assessment":null,"coverage":{"examined":false,"on":[],"note":"No judgment of this node is in force. That is not a finding either way."},"quantity":null,"threshold_of":null,"question":null,"formalization":null,"formalization_pending":null,"formalization_history":[],"verification":null,"lean_checks":[],"lean_checks_total":0,"waiting_messages":[{"trigger":"structure_and_assess","from":"the system","sender_node_id":null,"sent_at":"2026-11-13T21:47:43.154Z","paid":false,"summary":"New claim onboarded. Give it the structure and assessment its importance warrants; a minor or settled claim may need no decomposition."},{"trigger":"mandate_plan","from":"a mandate's plan","sender_node_id":null,"sent_at":"2026-11-14T06:38:05.598Z","paid":true,"summary":"First assessment. The parent question's pass named the main gap: the ICML 2026 cross-context consistency paper (Lin et al., 'Same Question, Different Lies') and arXiv 2611.14950 were read only as abst…"}],"requests":[],"requests_total":0,"subclaim_count":0,"instance_count":0,"source_map":null,"dependents":[{"id":"bda65b89-5ecb-4728-bfe9-0b54ee7fbc25","text":"Under what conditions can evaluators reliably detect language models deliberately underperforming capability evaluations?","claim_type":"empirical_derived","node_kind":"question","relation_type":"answers","reasoning":"The condition for evaluators without weight access: chain-of-thought and transcript monitors catch sandbagging that is reasoned about in the open, consistency checks catch sandbagging that varies across paraphrases, and neither has been shown to catch a model trained to reproduce a weaker model's output distribution.","importance":0.55,"assessment_status":null,"assessment_confidence":null,"assessment_credence":null,"bounty_micro_usd":null,"checked":null,"formal":false}],"dependents_total":1,"related":[],"subclaims":[],"subclaims_assessed":0,"arguments":[],"findings":[]}

get_claim_instances

{
  "claim_id": "022b9cef-1397-4f4c-af7e-917df64bab6b"
}

{
  "claim_id": "022b9cef-1397-4f4c-af7e-917df64bab6b",
  "total": 0,
  "limit": 20,
  "offset": 0,
  "has_more": false,
  "instances": []
}