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Unassisted Noise-Reduction of Chemical Reactions Data Sets
<p>Existing deep learning models applied to reaction prediction in organic chemistry can reach high levels of accuracy (> 90% for Natural Language Processing-based ones).</p><p>With no chemical knowledge embedded than the information learnt from reaction data, the quality of the data sets plays a crucial role in the performance of the prediction models. While human curation is prohibitively expensive, the need for unaided approaches to remove chemically incorrect entries from existing data setsdoi:10.26434/chemrxiv.12395120.v2 fatcat:xvdfiyq3fjgbpdtvocytoqt5vu