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Models, parameterization, and software: epistemic opacity in computational chemistry

Wieber, Frederic and Hocquet, Alexandre (2020) Models, parameterization, and software: epistemic opacity in computational chemistry. Perspectives on Science, 28 (5). pp. 610-629. ISSN 1063-6145

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Abstract

Computational chemistry grew in a new era of "desktop modeling", which coincided with a growing demand for modeling software, especially from the pharmaceutical industry. Parameterization of models in computational chemistry is an arduous enterprise, and we argue that this activity leads, in this specific context, to tensions among scientists regarding the lack of epistemic transparency of parameterized methods and the software implementing them. We relate one flame war from the Computational Chemistry mailing List in order to assess in detail the relationships between modeling methods, parameterization, software and the various forms of their enclosure or disclosure. Our claim is that parameterization issues are a source of epistemic opacity and that this opacity is entangled in methods and software alike. Models and software must be addressed together to understand the epistemological tensions at stake.


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Item Type: Published Article or Volume
Creators:
CreatorsEmailORCID
Wieber, Frederic0000-0001-7167-9813
Hocquet, Alexandre0000-0001-6361-5780
Keywords: Computational chemistry; models; software; parameterization; epistemic opacity
Subjects: Specific Sciences > Chemistry
Specific Sciences > Computer Science
General Issues > Computer Simulation
General Issues > History of Science Case Studies
General Issues > Models and Idealization
General Issues > Science and Society
Depositing User: Frederic Wieber
Date Deposited: 26 Mar 2021 13:21
Last Modified: 26 Mar 2021 13:21
Item ID: 18857
Journal or Publication Title: Perspectives on Science
Publisher: MIT Press
Official URL: https://doi.org/10.1162/posc_a_00352
DOI or Unique Handle: 10.1162/posc_a_00352
Subjects: Specific Sciences > Chemistry
Specific Sciences > Computer Science
General Issues > Computer Simulation
General Issues > History of Science Case Studies
General Issues > Models and Idealization
General Issues > Science and Society
Date: October 2020
Page Range: pp. 610-629
Volume: 28
Number: 5
ISSN: 1063-6145
URI: http://philsci-archive.pitt.edu/id/eprint/18857

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