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  Machine Learning for the History of Ideas

Brausch, S., & Graßhoff, G. (2023). Machine Learning for the History of Ideas. Future Humanities, 1(1, Article E6): E6. doi:10.1002/fhu2.6.

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Item Permalink: https://hdl.handle.net/21.11116/0000-000D-44BE-1 Version Permalink: https://hdl.handle.net/21.11116/0000-000F-6D93-1
Genre: Journal Article

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Future Humanities - 2023 - Brausch - Machine learning for the history of ideas.pdf (Publisher version), 2MB
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https://hdl.handle.net/21.11116/0000-000D-44C0-D
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Future Humanities - 2023 - Brausch - Machine learning for the history of ideas.pdf
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https://creativecommons.org/licenses/by/4.0/

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https://onlinelibrary.wiley.com/doi/10.1002/fhu2.6 (Any fulltext)
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 Creators:
Brausch, Simon1, Author           
Graßhoff, Gerd2, Author                 
Affiliations:
1Max Planck Research Group Practices of Validation in the Biomedical Sciences, Max Planck Institute for the History of Science, Max Planck Society, ou_3309453              
2Max Planck Fellow Computational History of Science, Max Planck Institute for the History of Science, Max Planck Society, ou_2443691              

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Language(s): eng - English
 Dates: 2023-06-072023-04
 Publication Status: Issued
 Pages: 22
 Publishing info: -
 Table of Contents: -
 Rev. Type: -
 Identifiers: DOI: 10.1002/fhu2.6
 Degree: -

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Title: Future Humanities
Source Genre: Journal
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Publ. Info: Wiley
Pages: - Volume / Issue: 1 (1, Article E6) Sequence Number: E6 Start / End Page: - Identifier: ISSN: 2770-2030