Step 2: tool results

get_claim

{
  "include": [
    "arguments",
    "subclaims",
    "dependents"
  ],
  "claim_id": "a3a7a95b-f3fb-4cf8-a605-cbe3bee834db"
}

{"claim":{"id":"a3a7a95b-f3fb-4cf8-a605-cbe3bee834db","kind":"claim","canonical_form":"AI systems perform a large and rapidly growing share of AI research and development at frontier labs.","claim_type":"empirical_derived","state":"active","decomposition_status":"complete","importance":0.6,"contestation":0.4,"domains":[],"tags":[{"slug":"ai-research-automation","name":"AI Research Automation"},{"slug":"artificial-intelligence","name":"Artificial intelligence"}],"steward_state":"running","stewarded_at":"2026-11-14T19:36:08.204Z","canonical_direction_note":"This affirmative wording states the disputed thesis that AI systems already perform a substantial and rapidly increasing fraction of frontier-lab AI R&D.","created_at":"2026-11-14T02:37:11.341Z","updated_at":"2026-11-14T19:36:05.518Z","page_url":"https://minerval.ai/claims/a3a7a95b-f3fb-4cf8-a605-cbe3bee834db"},"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":"2026-11-14T02:37:11.380Z","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":"2026-11-14T19:36:05.568Z","paid":true,"summary":"A funded mandate scheduled a assess pass on this claim."}],"requests":[],"requests_total":0,"subclaim_count":0,"instance_count":1,"source_map":null,"dependents":[{"id":"55f89371-8a43-43c1-8dd7-932c350ca7fb","text":"By the end of 2027, a frontier AI model will autonomously train a successor version of itself.","claim_type":"empirical_verifiable","node_kind":"claim","relation_type":"supports","reasoning":"A large and fast-growing AI share of AI R&D is the trend whose extrapolation underlies forecasts of autonomous successor training.","importance":0.7,"assessment_status":"doubtful","assessment_confidence":0.65,"assessment_credence":0.12,"bounty_micro_usd":null,"checked":null,"formal":false}],"dependents_total":1,"arguments":[],"subclaims":[],"subclaims_assessed":0,"unplaced_argument_passages":[{"instance_id":"71ee9105-c535-4cb7-83f5-56f6aa5ed600","source":{"id":"ece6f61a-093f-4e2c-ba9d-801d19e6370e","url":"https://forecastingresearch.substack.com/p/how-close-is-recursive-self-improvement","title":"How Close Is Recursive Self-Improvement?"},"verbatim_text":"At Anthropic, Claude wrote over 90% of contributions to the codebase in September 2026. At OpenAI, AI agents did 3.1 workdays of work for each human workday in August 2026, up from about 0.5 in May 2026.","context":null,"stance":"advances","direction":"for"}],"unplaced_argument_passages_total":1}