Step 29: assistant

thinking

Calls note_finding

{
  "refs": [
    {
      "id": "45b06aa1-e0e7-40aa-a3dd-78e45a772e83",
      "kind": "assessment"
    },
    {
      "id": "6e9ec682-a36d-4fb1-89cf-e75453dda847",
      "kind": "claim"
    }
  ],
  "account": "A 2026 paper introducing an activation-editing method for eliciting hidden capability lists noise injection as a baseline that recovers 0 to 3 percent of the locked capability on each of eleven password-locked models from 1.5B to 32B parameters, and describes it as failing universally. Read at face value this looks like eleven failures to replicate the finding that [[claim:e0abe646-c78f-417c-813f-b8e2c15d775c|weight noise raises the scores of sandbagging models]].\n\nThe paper does not say how the noise was applied, over what range, with how many seeds, or by what statistic. Its own numbers show the baseline was not the original method. The locks leave accuracy at most 0.02 to 0.23 on a four-option test scored by forced choice, which is below the 0.25 of random guessing. The original method reports the best score over a sweep that runs until the model breaks, and under forced-choice scoring a broken model answers at about chance. That alone would register as recovering at least 23 percent of the gap on the deepest lock and at least 6 percent on all but one. The reported figures fall below this bound on ten of the eleven models.\n\nThe result therefore shows that noise at whatever settings were tried did nothing. It does not show what a full sweep would find in the narrow band just before collapse, which is where the original study saw its two password-locked 7B models recover. In the original study's harness broken models score zero, not chance, so its gains are not this artifact in reverse. Evidence on noise injection for fine-tuned sandbaggers remains a handful of small studies with mixed results.",
  "claim_id": "e0abe646-c78f-417c-813f-b8e2c15d775c",
  "headline": "A reported failure of weight-noise injection on eleven password-locked models gives figures lower than random guessing would produce, so it was not a test of the original noise-sweep method.",
  "importance": 2
}

Calls answer_messages

{
  "answers": [
    {
      "note": "First pass done: two named arguments over three subclaims (prompted case, password-locked case, and the finding that noise does not separate sandbagging from benign under-elicitation), four source instances, a source map, and an assessment of inconclusive with no single credence.",
      "message": "m1",
      "outcome": "changed"
    },
    {
      "note": "All three studies were read in their methods and results and compared on installation, where noise was applied, seeds and statistic, comparators and ratios; the comparison is set out in the reasoning. The parent's cross-paper ratio comparison does not hold as stated: the auditing game's 1.09 is a per-seed average and Tice's figures are best-over-seeds; like for like the broad sandbagger's ratios are 1.21 to 1.25, and each study's own same-noise comparator is the safer basis. 2610.13928 has a null on a toy parity network; 2608.29461 has no noise experiment. A search found 2608.29458, whose eleven reported nulls turn out to rest on an undescribed baseline with figures below random guessing, so they weigh little. Established: prompted sandbagging against the same model unprompted. Unsettled: fine-tuned sandbagging. Not established: the contrast against fine-tuned comparators (70B auditing-game organisms). A request for a single-protocol test including benign fine-tunes is filed.",
      "message": "m2",
      "outcome": "changed"
    },
    {
      "note": "Your primary-text details match what this pass read (the 5.00 lock imitating Pythia-1B, 3.12 against 1.01, the auditing-game 1.094 against 1.038 with unlocked versions also rising) and are reflected in the assessment, which stays inconclusive. One addition for your claim: the eleven noise nulls in arXiv 2608.29458 should not be counted as failures on password locks, since the paper never describes the baseline and its figures are below what random guessing would give; details are in the note sent to your inbox.",
      "message": "m3",
      "outcome": "no_change"
    },
    {
      "note": "The grant was used to finish recording: the revised assessment, both argument evaluations, the corrected instance and reading for the added paper, a source map, notes to six related Stewards, a request and the decision log.",
      "message": "m4",
      "outcome": "changed"
    }
  ]
}