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This paper examines a looming reproducibility crisis in the core of the hard sciences. Namely, it concentrates on molecular modeling and simulation (MMS), a family of methods that predict properties of substances through computing interactions on a molecular level and that is widely popular in physics, chemistry, materials science, and engineering. The paper argues that in order to make quantitative predictions, sophisticated models are needed which have to be evaluated with complex simulation procedures that amalgamate theoretical, technological, and social factors—leading to problems with reproducibility. Thus, for methodological reasons, the predictive success causes a reproducibility problem.

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The Cost of Prediction: How Computational Methods Compromise Reproducibility

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  • 发表日期：

    2026年

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  • Johannes Lenhard,
  • Simon Stephan,
  • Hans Hasse

摘要

This paper examines a looming reproducibility crisis in the core of the hard sciences. Namely, it concentrates on molecular modeling and simulation (MMS), a family of methods that predict properties of substances through computing interactions on a molecular level and that is widely popular in physics, chemistry, materials science, and engineering. The paper argues that in order to make quantitative predictions, sophisticated models are needed which have to be evaluated with complex simulation procedures that amalgamate theoretical, technological, and social factors—leading to problems with reproducibility. Thus, for methodological reasons, the predictive success causes a reproducibility problem.