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Quantitative measurement is an accepted ideal, but pass–fail inspection remains a fact of life, even in high-technology industries. For pass–fail data, variance components do not separate gauge and material variation. This article focuses on maximum likelihood estimation of conditional misclassification rates, with and without reference evaluations to anchor the analysis. Likelihood-based confidence intervals and testing for reproducibility effects are also discussed.
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Stored only when both papers are in the corpus — 41 citations exist upstream.
Papers that cite the same references — the relational fallback while embeddings are still backfilling.
Imported from OpenAlex (CC0) — nothing here is generated.