records whether its decision beat noise
Two things the maintainer was right about.
Thinking was disabled so `temperature: 0` would not be silently ignored --
a trade that only pays if it buys determinism. Round zero says it did not:
11 of 20 injection pairs disagreed with themselves across five runs, so the
variance is in the agentic path, not the decoder. We paid the reasoning cost
on a reasoning model and got nothing. It is now `[learning] thinking`,
recorded in the artifact and part of its key so the two modes cannot be read
as one number. The default stays off only because that is what round zero
was measured under.
And the deeper point: the spec built `sign_test` and `reliable_change` and
the acceptance rule calls neither -- `decide` compares raw deltas. On a
detector with that floor a raw delta is mostly noise, and a rule that
brittle is exactly what makes a deterministic decoder look necessary. It is
not; the alternative is an acceptance rule that models the score as noisy,
the way reflective-evolution and Bayesian prompt optimizers do. Changing
Req 9.5 is a maintainer's call, so this does not change the decision: every
round now journals the two-sided sign test over the pairs that moved, and
after four rounds the journal will say whether any decision could be told
from a coin flip.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
OpenAI-shaped providers put `logprobs` beside the message rather than
inside it, so the confidence signal the classifier is meant to abstain on
was always None -- a knob that reads 'never unsure' whatever the model said.
Measured against DeepSeek while checking: it returns the structure but not
the values. Every chosen token comes back at logprob 0.0 and every
alternative at -9999.0, on a deliberately uncertain prompt as much as a
certain one. The field is there; the information is not.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
Task 1.2. Detectors, the classifier's model tier, the proposer and the judge
resolve one chat endpoint: an explicit override first, then the scripted client
flag, then an endpoint named in the config, then DeepSeek, then OpenRouter.
Prove-order retrieval keeps its own embedding endpoint untouched, because the
chat provider we default to offers none.
The adapter handles the provider's documented quirks: thinking is on by default
there and silently ignores temperature, so it is disabled explicitly; the
reasoning field is kept on the reply for the caller to replay across tool turns;
JSON mode has no schema and occasionally returns empty content, so one retry is
built in, never a loop; token log-probabilities are requested only when the
caller wants them, and their mean is what lets the classifier abstain.
Cost comes from the provider's own usage fields, cache hits priced separately,
and a model with no recorded price reports no cost rather than a made-up one.
The endpoint record deliberately holds no key, so it is safe to journal.
Co-Authored-By: Claude Opus 5 (1M context) <[email protected]>
Claude-Session: https://claude.ai/code/session_01T7XD7x5KonMdmGRkp63EQG
