Run step
Step 18: tool results
notify_steward
Input
{
"message": "First assessment of the answer on dividing work between SAE and LLM methods: supported, confidence 0.55, credence 0.6. It has been reworded to \"In API-only model diffing, SAE methods suit token- and formatting-level output differences, while LLM methods suit abstract behavioral ones.\" The evidence is one study (Kempf et al. 2026), one SAE pipeline and abstraction scores from LLM raters. The split is the authors' interpretation, and there are counter-cases both inside and outside the paper. What it records is the level at which each method reports differences. It does not show that SAEs win on anything.",
"claim_id": "653e653c-cda0-4e4c-bfe2-de7f99acee34",
"target_ids": [
"6b0dcfde-1ad4-4608-83ac-8e5c1dc1dbf2"
]
}{"success":true,"message":"Sent to the Steward of 1 node(s) as a note. Each waits in that node's inbox, shown on its page and to its funders, until a pass reads it.","notified":[{"id":"6b0dcfde-1ad4-4608-83ac-8e5c1dc1dbf2","kind":"question","trigger":"subclaim_change"}]}