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Machine Learning May Sometimes Simply Capture Literature Popularity Trends: A Case Study of Heterocyclic Suzuki–Miyaura Coupling
[Image: see text] Applications of machine learning (ML) to synthetic chemistry rely on the assumption that large numbers of literature-reported examples should enable construction of accurate and predictive models of chemical reactivity. This paper demonstrates that abundance of carefully curated li...
| Autores principales: | , , , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
American Chemical Society
2022
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| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8949728/ https://www.ncbi.nlm.nih.gov/pubmed/35258973 http://dx.doi.org/10.1021/jacs.1c12005 |