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Open Access Error Assessment of Computational Models in Chemistry

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Computational models in chemistry rely on a number of approximations. The effect of such approximations on observables derived from them is often unpredictable. Therefore, it is challenging to quantify the uncertainty of a computational result, which, however, is necessary to assess the suitability of a computational model. Common performance statistics such as the mean absolute error are prone to failure as they do not distinguish the explainable (systematic) part of the errors from their unexplainable (random) part. In this paper, we discuss problems and solutions for performance assessment of computational models based on several examples from the quantum chemistry literature. For this purpose, we elucidate the different sources of uncertainty, the elimination of systematic errors, and the combination of individual uncertainty components to the uncertainty of a prediction.
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Document Type: Research Article

Affiliations: 1: ETH Zürich Laboratorium für Physikalische Chemie Vladimir-Prelog-Weg 2, CH-8093 Zurich 2: ETH Zürich Laboratorium für Physikalische Chemie Vladimir-Prelog-Weg 2, CH-8093 Zurich;, Email: [email protected]

Publication date: April 1, 2017

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  • International Journal for Chemistry and Official Membership Journal of the Swiss Chemical Society (SCS) and its Divisions

    CHIMIA, a scientific journal for chemistry in the broadest sense, is published 10 times a year and covers the interests of a wide and diverse readership. Contributions from all fields of chemistry and related areas are considered for publication in the form of Review Articles and Notes. A characteristic feature of CHIMIA are the thematic issues, each devoted to an area of great current significance.

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