{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T09:15:13Z","timestamp":1765185313968,"version":"3.46.0"},"reference-count":49,"publisher":"American Chemical Society (ACS)","issue":"23","license":[{"start":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T00:00:00Z","timestamp":1763683200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T00:00:00Z","timestamp":1763683200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T00:00:00Z","timestamp":1763683200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-045"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J. Chem. Inf. Model."],"published-print":{"date-parts":[[2025,12,8]]},"DOI":"10.1021\/acs.jcim.5c02054","type":"journal-article","created":{"date-parts":[[2025,11,21]],"date-time":"2025-11-21T05:13:17Z","timestamp":1763701997000},"page":"12775-12785","source":"Crossref","is-referenced-by-count":0,"title":["Robust Chemical Reaction Condition Recommendations via Label Mix Strategy"],"prefix":"10.1021","volume":"65","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-5919-5904","authenticated-orcid":true,"given":"Xin","family":"Yan","sequence":"first","affiliation":[{"name":"ChemLex","place":["Shanghai, China"]}]},{"ORCID":"https:\/\/orcid.org\/0009-0001-3834-7777","authenticated-orcid":true,"given":"Haowen","family":"Zhong","sequence":"additional","affiliation":[{"name":"ChemLex","place":["Shanghai, China"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7231-9841","authenticated-orcid":true,"given":"Xiaoxue","family":"Wang","sequence":"additional","affiliation":[{"name":"ChemLex","place":["Shanghai, China"]}]}],"member":"316","published-online":{"date-parts":[[2025,11,21]]},"reference":[{"key":"ref1\/cit1","doi-asserted-by":"publisher","DOI":"10.1038\/s41557-018-0021-z"},{"key":"ref2\/cit2","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-025-59812-0"},{"key":"ref3\/cit3","doi-asserted-by":"publisher","DOI":"10.1038\/s41586-021-03213-y"},{"key":"ref4\/cit4","doi-asserted-by":"publisher","DOI":"10.1126\/science.adc8743"},{"key":"ref5\/cit5","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-024-00834-z"},{"key":"ref6\/cit6","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/btr413"},{"key":"ref7\/cit7","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-025-00953-1"},{"key":"ref8\/cit8","doi-asserted-by":"publisher","DOI":"10.1021\/acs.orglett.3c01282"},{"key":"ref9\/cit9","unstructured":"Current, S.; Chen, Z.; Adu-Ampratwum, D.; Ning, X.; Parthasarathy, S. Parthasarathy, S. DiffER: Categorical Diffusion for Chemical Retrosynthesis, arXiv:2505.23721. arXiv.org e-Print archive https:\/\/arxiv.org\/abs\/2505.23721, 2025."},{"key":"ref10\/cit10","doi-asserted-by":"publisher","DOI":"10.1002\/minf.202100294"},{"key":"ref11\/cit11","doi-asserted-by":"publisher","DOI":"10.1021\/c160017a018"},{"key":"ref12\/cit12","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.9b00313"},{"key":"ref13\/cit13","doi-asserted-by":"publisher","DOI":"10.3390\/ijms23010248"},{"key":"ref14\/cit14","doi-asserted-by":"publisher","DOI":"10.1039\/D1SC06932B"},{"key":"ref15\/cit15","doi-asserted-by":"publisher","DOI":"10.1021\/acscentsci.8b00357"},{"key":"ref16\/cit16","doi-asserted-by":"publisher","DOI":"10.1039\/C8SC04228D"},{"key":"ref17\/cit17","doi-asserted-by":"crossref","unstructured":"Ahmadian, S.; Berahmand, K.; Rostami, M.; Forouzandeh, S.; Moradi, P.; Jalili, M. Recommender Systems based on Non-negative Matrix Factorization: A Survey. In\n                      IEEE Transactions on Artificial Intelligence\n                      , 2025.","DOI":"10.1109\/TAI.2025.3559053"},{"key":"ref18\/cit18","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.0c01234"},{"key":"ref19\/cit19","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.2c01085"},{"key":"ref20\/cit20","doi-asserted-by":"publisher","DOI":"10.1039\/D4SC05946H"},{"key":"ref21\/cit21","doi-asserted-by":"publisher","DOI":"10.1016\/j.eswa.2024.125534"},{"key":"ref22\/cit22","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-031-99267-4_10"},{"key":"ref23\/cit23","doi-asserted-by":"publisher","DOI":"10.1039\/D2SC06798F"},{"key":"ref24\/cit24","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-024-00805-4"},{"key":"ref25\/cit25","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.0c01234"},{"key":"ref26\/cit26","doi-asserted-by":"publisher","DOI":"10.34133\/research.0231"},{"key":"ref27\/cit27","doi-asserted-by":"publisher","DOI":"10.1039\/C9SC05704H"},{"key":"ref28\/cit28","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jcim.2c01407"},{"key":"ref29\/cit29","doi-asserted-by":"publisher","DOI":"10.1039\/D3SC01604H"},{"key":"ref30\/cit30","doi-asserted-by":"crossref","unstructured":"Qian, Y.; Li, Z.; Tu, Z.; Coley, C.; Barzilay, R.Predictive Chemistry Augmented with Text Retrieval. In\n                      Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing. Singapore\n                      , 2023; pp 12731\u201312745.","DOI":"10.18653\/v1\/2023.emnlp-main.784"},{"key":"ref31\/cit31","unstructured":"Zhang, Y.; Yu, R.; Zeng, K.; Li, D.; Zhu, F.; Yang, X.; Jin, Y.; Xu, Y.\n                      Text-Augmented Multimodal LLMs for Chemical Reaction Condition Recommendation\n                      , 2024, arXiv:2407.15141. arXiv.org e-Print archive https:\/\/arxiv.org\/abs\/2407.15141."},{"key":"ref32\/cit32","unstructured":"Chen, K.; Li, J.; Wang, K.; Du, Y.; Yu, J.; Lu, J.; Li, L.; Qiu, J.; Fang, Q.; Heng, P.A. Towards an automatic AI agent for reaction condition recommendation in chemical synthesis. In\n                      CoRR\n                      , 2023."},{"key":"ref33\/cit33","doi-asserted-by":"publisher","DOI":"10.1021\/acs.iecr.3c02520"},{"key":"ref34\/cit34","doi-asserted-by":"publisher","DOI":"10.1038\/s42256-020-00284-w"},{"key":"ref35\/cit35","doi-asserted-by":"publisher","DOI":"10.1039\/C9SC04944D"},{"key":"ref36\/cit36","unstructured":"Lowe, D. M. Extraction of chemical structures and reactions from the literature. Diss, 2012."},{"key":"ref37\/cit37","doi-asserted-by":"publisher","DOI":"10.1186\/s13321-020-0416-x"},{"key":"ref38\/cit38","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-18671-7"},{"key":"ref39\/cit39","unstructured":"Zhang, H.; Cisse, M.; Dauphin, Y. N.; Lopez-Paz, D. mixup: Beyond empirical risk minimization, 2017, arXiv:1710.09412. arXiv.org e-Print archive https:\/\/arxiv.org\/abs\/1710.09412."},{"key":"ref40\/cit40","unstructured":"Ye, T.; Dong, L.; Xia, Y.; Sun, Y.; Zhu, Y.; Huang, G.; Wei, F. Differential Transformer. In\n                      Thirteenth International Conference on Learning Representations\n                      ."},{"key":"ref41\/cit41","unstructured":"Kipf, T. N.; Welling, M. Semi-supervised classification with graph convolutional networks, 2016, arXiv:1609.02907. arXiv.org e-Print archive https:\/\/arxiv.org\/abs\/1609.02907."},{"key":"ref42\/cit42","unstructured":"Gilmer, J.; Schoenholz, S. S.; Riley, P. F.; Vinyals, O.; Dahl, G. E.Neural message passing for quantum chemistry. In\n                      International Conference on Machine Learning\n                      , 2017; pp 1263\u20131272."},{"key":"ref43\/cit43","doi-asserted-by":"crossref","unstructured":"Lin, Z.; Pan, J.; Zhang, S.; Wang, X.; Xiao, X.; Huang, S.; Xiao, L.; Jiang, J.Understanding the Ranking Loss for Recommendation with Sparse User Feedback. In\n                      Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining. New York, NY, USA\n                      , 2024; pp 5409\u20135418.","DOI":"10.1145\/3637528.3671565"},{"key":"ref44\/cit44","doi-asserted-by":"publisher","DOI":"10.3762\/bjoc.20.212"},{"key":"ref45\/cit45","unstructured":"Ryou, S.; Maser, M. R.; Cui, A. Y.; DeLano, T. J.; Yue, Y.; Reisman, S. E.\n                      Graph neural networks for the prediction of substrate-specific organic reaction conditions\n                      , 2020, arXiv:2007.04275. arXiv.org e-Print archive https:\/\/arxiv.org\/abs\/2007.04275."},{"key":"ref46\/cit46","doi-asserted-by":"publisher","DOI":"10.1039\/D4SC05946H"},{"key":"ref47\/cit47","doi-asserted-by":"publisher","DOI":"10.1039\/D5SC04957A"},{"key":"ref48\/cit48","doi-asserted-by":"publisher","DOI":"10.1126\/science.aar5169"},{"key":"ref49\/cit49","unstructured":"Mayfield, J.; Lowe, D.; Sayle, R. Pistachio. Patent. [Online], 2018, Available: https:\/\/www.nextmovesoftware.com\/pistachio.html."}],"container-title":["Journal of Chemical Information and Modeling"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acs.jcim.5c02054","content-type":"application\/pdf","content-version":"vor","intended-application":"unspecified"},{"URL":"https:\/\/pubs.acs.org\/doi\/pdf\/10.1021\/acs.jcim.5c02054","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,12,8]],"date-time":"2025-12-08T09:10:47Z","timestamp":1765185047000},"score":1,"resource":{"primary":{"URL":"https:\/\/pubs.acs.org\/doi\/10.1021\/acs.jcim.5c02054"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,21]]},"references-count":49,"journal-issue":{"issue":"23","published-print":{"date-parts":[[2025,12,8]]}},"alternative-id":["10.1021\/acs.jcim.5c02054"],"URL":"https:\/\/doi.org\/10.1021\/acs.jcim.5c02054","relation":{},"ISSN":["1549-9596","1549-960X"],"issn-type":[{"type":"print","value":"1549-9596"},{"type":"electronic","value":"1549-960X"}],"subject":[],"published":{"date-parts":[[2025,11,21]]}}}