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. 2023 Oct 3;14:6155. doi: 10.1038/s41467-023-41698-5

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© The Author(s) 2023

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Fig. 6 — a–d Hidden features are derived based on two criteria: (1) whether the reaction type is recognized, and (2) the origin of the hidden features (either from the reaction center predictor, RCP, layer, or the leaving group matcher, LGM, layer). Subsequently, these features are reduced to two dimensions using t-SNE techniques. Distinct colors represent various reaction types, while diverse styles are assigned based on the maximum count of hydrogen alterations.