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A full preprint synthesizing riddled-basin geometry (Ly & Gong, Nature Machine Intelligence 2026) with PAC-Bayes certification: when training outcomes are unpredictable at the seed level, the correct reliability instrument is a bound that holds for the trained model itself. Measured: a three-round governed distillation arc (0.3%, 2.7%, 1.3% gate-assisted - assistance made acceptance worse), a null uncertainty-exponent measurement with its design flaw named, and the synthesis that certification is basin-independent by construction.
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Stephen P. Lutar (2026) studied this question.
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