Step 18: tool results

match_claim

{
  "text": "As of late 2026, frontier AI agents cannot yet carry out open-ended AI research without human research judgment.",
  "exclude_claim_id": "55f89371-8a43-43c1-8dd7-932c350ca7fb"
}

{"outcome":"new","is_match":false,"matched_claim_id":null,"instance_stance":"affirms","new_canonical_form":"Human research judgment remains necessary for open-ended frontier AI research as of late 2026.","direction_note":"This states the affirmative thesis of continued human-judgment dependence, rather than framing it as a denial of agent capability.","confidence":0.9,"reasoning":"The source asserts that frontier agents cannot conduct open-ended AI research without human research judgment. The closest existing claim, “As of late 2026, humans supply most research judgment in frontier AI R&D” (d479cf4d-52b6-4260-a3dc-7a2e5a812d42), concerns the observed allocation of judgment: humans supply most of it. That does not establish that human judgment is necessary for carrying out open-ended research, and autonomous agents could be capable of doing so even if humans currently perform most judgment. Conversely, humans might supply a minority of judgment while still providing an indispensable contribution. The existing claim that agents perform research engineering but struggle with critical stages of the research lifecycle (81eeb61b-4ce4-4d0b-891d-11e970d8f669), and the claim about recurring failures during open-ended research (7064aebc-8735-45b1-9ee7-523e919cb15a), describe capability limitations or failure patterns, not the stronger necessity proposition. The evidence-thin claim (d91e5ad8-8ffd-4fb2-8507-ee86b736c75f) is about the state of evidence, not the capability itself. These are closely related claims, but the propositions turn on different considerations; the source affirms the new canonical claim.","alternative_matches":["d479cf4d-52b6-4260-a3dc-7a2e5a812d42","81eeb61b-4ce4-4d0b-891d-11e970d8f669","7064aebc-8735-45b1-9ee7-523e919cb15a","d91e5ad8-8ffd-4fb2-8507-ee86b736c75f","27a33dd0-42b0-48e8-aead-a838e382a200"],"relationship_notes":"d479cf4d-52b6-4260-a3dc-7a2e5a812d42 concerns who currently supplies most research judgment, a related but distinct allocation claim; 81eeb61b-4ce4-4d0b-891d-11e970d8f669 and 7064aebc-8735-45b1-9ee7-523e919cb15a concern agent performance and recurring failures, which may support but do not entail human judgment being necessary; d91e5ad8-8ffd-4fb2-8507-ee86b736c75f concerns evidential thinness; 27a33dd0-42b0-48e8-aead-a838e382a200 concerns autonomous engineering completion, not open-ended research judgment."}

match_claim

{
  "text": "Frontier AI developers will not run a frontier model's training without human oversight even once AI could do it autonomously.",
  "exclude_claim_id": "55f89371-8a43-43c1-8dd7-932c350ca7fb"
}

{"outcome":"new","is_match":false,"matched_claim_id":null,"instance_stance":"affirms","new_canonical_form":"Frontier AI developers will retain human oversight of frontier model training after AI can perform it autonomously.","direction_note":"This states the affirmative forecast that human oversight of frontier training will persist even after AI can perform training autonomously.","confidence":0.94,"reasoning":"I searched the source wording, paraphrases, and the opposite scenario. The closest existing nodes concern different propositions: AI becoming capable of fully automating frontier AI research (f07e018c-7df9-4db6-972c-d7feb111e699), the emergence of significant autonomous contributions to frontier-model training within a specified period (c8f360ce-76e9-4a95-aa02-e32c4421e4e6), and current human roles in AI research or the broader trajectory toward automation (d479cf4d-52b6-4260-a3dc-7a2e5a812d42; 6be5b967-9784-4985-8413-928665429119). Those claims concern AI capability/contribution or human involvement at present and in general; none asserts whether frontier developers will maintain human oversight of training once autonomous training is possible. The source directly affirms the proposed new claim, not its negation. The proposed wording expresses the same forecast in a neutral affirmative direction.","alternative_matches":["f07e018c-7df9-4db6-972c-d7feb111e699","c8f360ce-76e9-4a95-aa02-e32c4421e4e6","d479cf4d-52b6-4260-a3dc-7a2e5a812d42","6be5b967-9784-4985-8413-928665429119"],"relationship_notes":"The closest matches are related but distinct: f07e018c-7df9-4db6-972c-d7feb111e699 concerns capability for full research automation; c8f360ce-76e9-4a95-aa02-e32c4421e4e6 concerns autonomous contribution to model training; d479cf4d-52b6-4260-a3dc-7a2e5a812d42 concerns present human research judgment; and 6be5b967-9784-4985-8413-928665429119 broadly concerns automation alongside continued human direction and evaluation. This new claim is a specific prediction about developers' oversight practice after autonomous training becomes feasible."}