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The quality of data must be known and established before it can be used logically in any application. Data quality may be judged on the basis of its quantiative accuracy and on the confidence that can be placed in the qualitative identification of the parameters measured. This requires the production of data in a quality assurance program that permits the assignment of its statistically supported limits of uncertainty. The essential features of such a program, consisting of quality control and quality assessment techniques, are discussed in the paper.
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Stored only when both papers are in the corpus — 11 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.