Step 2: tool results

get_claim

{
  "include": [
    "arguments",
    "subclaims",
    "dependents"
  ],
  "claim_id": "c016ed07-5d53-45a4-b4a9-a7a0c3f2413e"
}

{"claim":{"id":"c016ed07-5d53-45a4-b4a9-a7a0c3f2413e","kind":"claim","canonical_form":"AI software progress is well described by a semi-endogenous idea-production model with a single stable returns-to-research parameter.","claim_type":"empirical_derived","state":"active","decomposition_status":"complete","importance":0.4,"contestation":0.6,"domains":[],"tags":[],"steward_state":"running","stewarded_at":"2026-11-11T23:18:27.942Z","canonical_direction_note":null,"created_at":"2026-11-11T23:12:38.974Z","updated_at":"2026-11-11T23:17:46.021Z","page_url":"https://minerval.ai/claims/c016ed07-5d53-45a4-b4a9-a7a0c3f2413e"},"assessment":null,"coverage":{"examined":false,"on":[],"note":"No judgment of this node is in force. That is not a finding either way."},"preliminary_seed":{"credence":0.35,"note":"The model (software efficiency growing with cumulative research input at constant elasticity) was built for economy-wide productivity with inputs growing a few percent a year. For AI software it leaves out the experimental compute that research consumes, limits on how far research can be parallelized, and spillovers between subfields, and the data are too coarse to test whether the elasticity has been constant. Those who fit it to AI domains describe it as plausibly badly misspecified for the uses made of it. It may still be a serviceable first approximation over the historical range, which is why the prior is not lower.","seeded_by_claim_id":"9bd7980e-665a-49ba-80a3-487fea7e764e"},"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":"2026-11-11T23:12:39.476Z","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":"2026-11-11T23:17:46.027Z","paid":true,"summary":"A funded mandate scheduled a pass on this claim."}],"requests":[],"requests_total":0,"subclaim_count":0,"instance_count":0,"source_map":null,"dependents":[{"id":"9bd7980e-665a-49ba-80a3-487fea7e764e","text":"Each doubling of cumulative AI software research input yields more than one doubling of software efficiency (returns parameter r > 1).","claim_type":"empirical_derived","node_kind":"claim","relation_type":"assumes","reasoning":"A returns parameter r exists only inside this framework. If AI software progress does not follow a constant-elasticity law in cumulative research input, the question whether r exceeds one has no determinate answer.","importance":0.6,"assessment_status":"inconclusive","assessment_confidence":0.7,"assessment_credence":0.6,"bounty_micro_usd":null,"checked":null,"formal":false}],"dependents_total":1,"subclaims":[],"subclaims_assessed":0,"arguments":[]}