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The paper considers the task of automatic expansion of the empirical states set by non-identical states from the collection in W@DIS information system. The relevance of this task is caused by long terms of preparation of new versions of empirical states, as a result of which new collections data cannot be automatically evaluated. The content and structure of collections of states and transitions for the H2O molecule are discussed. An algorithm for filtering data sources from collections and some rules for creating a set of unique quasi-empirical states are described, as well as the effects of filtering collections of transitions and states on their quality. As a result of such filtering, the number of inconsistent identical states and transitions in the collections was significantly reduced.

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Data Quality Assessment in Large Spectral Data Collections. States and Transitions

  • 会议论文

  • 发表日期：

    2026年

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  • Alexey Yu. Akhlyostin,
  • Nikolai A. Lavrentiev,
  • Alexey I. Privezentzev,
  • Alexander Z. Fazliev

摘要

The paper considers the task of automatic expansion of the empirical states set by non-identical states from the collection in W@DIS information system. The relevance of this task is caused by long terms of preparation of new versions of empirical states, as a result of which new collections data cannot be automatically evaluated. The content and structure of collections of states and transitions for the H2O molecule are discussed. An algorithm for filtering data sources from collections and some rules for creating a set of unique quasi-empirical states are described, as well as the effects of filtering collections of transitions and states on their quality. As a result of such filtering, the number of inconsistent identical states and transitions in the collections was significantly reduced.