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Buehler. It consistently frames results as the authors' reports rather than established fact.","excerpt":"Authors:Haiqian Yang, Markus J. Buehler"},{"dimension":"summary","status":"uncertain","explanation":"The core mechanics are clear, but the reading omits the motivation that makes the work matter to a general reader: specialized engineering knowledge is often proprietary and absent from LLM training data, so frontier models give generic answers. It also omits the authors' concluding thesis, a practical LLM+KG paradigm for private data, and their latent-state steering finding. 'Far exceeds' is softened to 'exceeds'. Smallest repair: add one sentence on the generic-answer and proprietary-knowledge problem, plus the authors' private-data paradigm claim.","excerpt":"often proprietary and absent from frontier LLM training data. In such domains, frontier models tend to give generic answers."},{"dimension":"date","status":"pass","explanation":"originalPublished 2026-10-27 matches the v1 submission date. The feed date of 2026-10-29 is later and correctly not used.","excerpt":"[Submitted on 27 Oct 2026]"},{"dimension":"support","status":"pass","explanation":"Each claim is directly supported by the abstract. The limitations about missing measurements are accurate for abstract-only evidence. 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