Step 10: tool results

match_claim

{
  "text": "Attribution graphs built from cross-layer transcoders showed that Claude 3.5 Haiku plans the rhyming word of a couplet's second line before writing it.",
  "exclude_claim_id": "4dbe502e-402c-4ae9-8c6f-57a252a0d324"
}

{"outcome":"new","is_match":false,"matched_claim_id":null,"instance_stance":"affirms","new_canonical_form":"Claude 3.5 Haiku represents a couplet’s intended rhyme word before generating its second line.","direction_note":"The proposition is stated affirmatively as the reported model behavior, rather than as a denial or merely as a question about whether it occurs.","confidence":0.93,"reasoning":"Searches using the exact wording, paraphrases focused on rhyme-word planning and future-token representations, the broader attribution-graph/cross-layer-transcoder framing, and the negation found no existing node about this specific behavior. The nearest results concern general language-model reasoning or other Claude behaviors, not whether Claude 3.5 Haiku represents a couplet’s rhyme word before producing its second line. This is a reusable factual proposition about a particular model and behavior, so it is a claim. The source explicitly presents the observed result as evidence that the model plans the rhyme word in advance, and therefore affirms the canonical proposition.","alternative_matches":["c8679034-719f-4714-9d9e-70e6d25e0eff","a4f885fe-4a61-4b47-ac02-a08e2a5b4a3d"],"relationship_notes":"The alternative claims concern language models' use of non-legible intermediate reasoning or anticipation of future training updates, respectively. They are broader or about different behaviors and do not state this specific rhyme-planning result."}

get_claim

{
  "claim_id": "33280953-bc40-496c-ab32-70e3cbfb6807"
}

{"claim":{"id":"33280953-bc40-496c-ab32-70e3cbfb6807","kind":"claim","canonical_form":"Randomly initialized frozen-component SAEs match fully trained SAEs on SAEBench sparse probing accuracy.","claim_type":"empirical_verifiable","state":"active","decomposition_status":"complete","importance":0.55,"contestation":0.5,"domains":[],"tags":[{"slug":"mechanistic-interpretability","name":"Mechanistic Interpretability"},{"slug":"large-language-models","name":"Large language models"}],"steward_state":"pending","stewarded_at":null,"canonical_direction_note":"The affirmative form states the reported finding that SAE baselines with randomly initialized frozen components achieve sparse-probing accuracy comparable to fully trained SAEs.","created_at":"2026-11-13T01:00:04.576Z","updated_at":"2026-11-13T01:00:04.722Z","page_url":"https://minerval.ai/claims/33280953-bc40-496c-ab32-70e3cbfb6807"},"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":"2026-11-13T01:00:04.727Z","paid":false,"summary":"New claim onboarded. Give it the structure and assessment its importance warrants; a minor or settled claim may need no decomposition."}],"requests":[],"requests_total":0,"subclaim_count":0,"instance_count":1,"source_map":null}