{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,7]],"date-time":"2026-05-07T00:30:38Z","timestamp":1778113838300,"version":"3.51.4"},"reference-count":62,"publisher":"Springer Science and Business Media LLC","issue":"12","license":[{"start":{"date-parts":[[2022,12,8]],"date-time":"2022-12-08T00:00:00Z","timestamp":1670457600000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2022,12,8]],"date-time":"2022-12-08T00:00:00Z","timestamp":1670457600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Nat Mach Intell"],"DOI":"10.1038\/s42256-022-00574-5","type":"journal-article","created":{"date-parts":[[2022,12,8]],"date-time":"2022-12-08T12:03:32Z","timestamp":1670501012000},"page":"1209-1223","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":18,"title":["A generalizable deep learning framework for inferring fine-scale germline mutation rate maps"],"prefix":"10.1038","volume":"4","author":[{"given":"Yiyuan","family":"Fang","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Shuyi","family":"Deng","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7843-2151","authenticated-orcid":false,"given":"Cai","family":"Li","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,12,8]]},"reference":[{"key":"574_CR1","doi-asserted-by":"publisher","first-page":"565","DOI":"10.1038\/nrg3241","volume":"13","author":"JA Veltman","year":"2012","unstructured":"Veltman, J. A. & Brunner, H. G. De novo mutations in human genetic disease. Nat. Rev. Genet. 13, 565\u2013575 (2012).","journal-title":"Nat. Rev. Genet."},{"key":"574_CR2","doi-asserted-by":"publisher","DOI":"10.1186\/s13059-016-1110-1","volume":"17","author":"R Acuna-Hidalgo","year":"2016","unstructured":"Acuna-Hidalgo, R., Veltman, J. A. & Hoischen, A. New insights into the generation and role of de novo mutations in health and disease. Genome Biol. 17, 241 (2016).","journal-title":"Genome Biol."},{"key":"574_CR3","doi-asserted-by":"publisher","first-page":"756","DOI":"10.1038\/nrg3098","volume":"12","author":"A Hodgkinson","year":"2011","unstructured":"Hodgkinson, A. & Eyre-Walker, A. Variation in the mutation rate across mammalian genomes. Nat. Rev. Genet. 12, 756\u2013766 (2011).","journal-title":"Nat. Rev. Genet."},{"key":"574_CR4","doi-asserted-by":"publisher","first-page":"919","DOI":"10.1038\/ng.3015","volume":"46","author":"S Schiffels","year":"2014","unstructured":"Schiffels, S. & Durbin, R. Inferring human population size and separation history from multiple genome sequences. Nat. Genet. 46, 919\u2013925 (2014).","journal-title":"Nat. Genet."},{"key":"574_CR5","doi-asserted-by":"publisher","first-page":"7","DOI":"10.1186\/s40709-017-0064-0","volume":"24","author":"P Pavlidis","year":"2017","unstructured":"Pavlidis, P. & Alachiotis, N. A survey of methods and tools to detect recent and strong positive selection. J. Biol. Res. (Thessalon.) 24, 7 (2017).","journal-title":"J. Biol. Res. (Thessalon.)"},{"key":"574_CR6","doi-asserted-by":"publisher","first-page":"310","DOI":"10.1038\/ng.2892","volume":"46","author":"M Kircher","year":"2014","unstructured":"Kircher, M. et al. A general framework for estimating the relative pathogenicity of human genetic variants. Nat. Genet. 46, 310\u2013315 (2014).","journal-title":"Nat. Genet."},{"key":"574_CR7","doi-asserted-by":"publisher","first-page":"1219","DOI":"10.1534\/genetics.109.105692","volume":"182","author":"PW Messer","year":"2009","unstructured":"Messer, P. W. Measuring the rates of spontaneous mutation from deep and large-scale polymorphism data. Genetics 182, 1219\u20131232 (2009).","journal-title":"Genetics"},{"key":"574_CR8","doi-asserted-by":"publisher","first-page":"e1006455","DOI":"10.1371\/journal.pgen.1006455","volume":"13","author":"YO Zhu","year":"2017","unstructured":"Zhu, Y. O., Sherlock, G. & Petrov, D. A. Extremely rare polymorphisms in Saccharomyces cerevisiae allow inference of the mutational spectrum. PLoS Genet. 13, e1006455 (2017).","journal-title":"PLoS Genet."},{"key":"574_CR9","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-018-05936-5","volume":"9","author":"J Carlson","year":"2018","unstructured":"Carlson, J. et al. Extremely rare variants reveal patterns of germline mutation rate heterogeneity in humans. Nat. Commun. 9, 3753 (2018).","journal-title":"Nat. Commun."},{"key":"574_CR10","doi-asserted-by":"publisher","first-page":"17916","DOI":"10.1073\/pnas.1900714116","volume":"116","author":"I Agarwal","year":"2019","unstructured":"Agarwal, I. & Przeworski, M. Signatures of replication timing, recombination, and sex in the spectrum of rare variants on the human X chromosome and autosomes. Proc. Natl Acad. Sci. USA 116, 17916\u201317924 (2019).","journal-title":"Proc. Natl Acad. Sci. USA"},{"key":"574_CR11","doi-asserted-by":"publisher","first-page":"349","DOI":"10.1038\/ng.3511","volume":"48","author":"V Aggarwala","year":"2016","unstructured":"Aggarwala, V. & Voight, B. F. An expanded sequence context model broadly explains variability in polymorphism levels across the human genome. Nat. Genet. 48, 349\u2013355 (2016).","journal-title":"Nat. Genet."},{"key":"574_CR12","doi-asserted-by":"publisher","first-page":"1679","DOI":"10.1101\/gr.287302","volume":"12","author":"Z Zhao","year":"2002","unstructured":"Zhao, Z. & Boerwinkle, E. Neighboring-nucleotide effects on single nucleotide polymorphisms: a study of 2.6 million polymorphisms across the human genome. Genome Res. 12, 1679\u20131686 (2002).","journal-title":"Genome Res."},{"key":"574_CR13","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-15185-0","volume":"11","author":"C Li","year":"2020","unstructured":"Li, C. & Luscombe, N. M. Nucleosome positioning stability is a modulator of germline mutation rate variation across the human genome. Nat. Commun. 11, 1363 (2020).","journal-title":"Nat. Commun."},{"key":"574_CR14","doi-asserted-by":"publisher","first-page":"47","DOI":"10.1146\/annurev-genom-031714-125740","volume":"15","author":"L Segurel","year":"2014","unstructured":"Segurel, L., Wyman, M. J. & Przeworski, M. Determinants of mutation rate variation in the human germline. Annu. Rev. Genomics Hum. Genet. 15, 47\u201370 (2014).","journal-title":"Annu. Rev. Genomics Hum. Genet."},{"key":"574_CR15","doi-asserted-by":"publisher","first-page":"434","DOI":"10.1038\/s41586-020-2308-7","volume":"581","author":"KJ Karczewski","year":"2020","unstructured":"Karczewski, K. J. et al. The mutational constraint spectrum quantified from variation in 141,456 humans. Nature 581, 434\u2013443 (2020).","journal-title":"Nature"},{"key":"574_CR16","doi-asserted-by":"publisher","first-page":"1634","DOI":"10.1038\/s41587-022-01353-8","volume":"40","author":"MA Sherman","year":"2022","unstructured":"Sherman, M. A. et al. Genome-wide mapping of somatic mutation rates uncovers drivers of cancer. Nat. Biotechnol. 40, 1634\u20131643 (2022).","journal-title":"Nat. Biotechnol."},{"key":"574_CR17","doi-asserted-by":"publisher","first-page":"101","DOI":"10.1038\/s41586-021-04269-6","volume":"602","author":"JG Monroe","year":"2022","unstructured":"Monroe, J. G. et al. Mutation bias reflects natural selection in Arabidopsis thaliana. Nature 602, 101\u2013105 (2022).","journal-title":"Nature"},{"key":"574_CR18","doi-asserted-by":"publisher","DOI":"10.1186\/gb-2008-9-4-r76","volume":"9","author":"S Tyekucheva","year":"2008","unstructured":"Tyekucheva, S. et al. Human-macaque comparisons illuminate variation in neutral substitution rates. Genome Biol. 9, R76 (2008).","journal-title":"Genome Biol."},{"key":"574_CR19","doi-asserted-by":"publisher","DOI":"10.1186\/gb-2011-12-6-r58","volume":"12","author":"CF Mugal","year":"2011","unstructured":"Mugal, C. F. & Ellegren, H. Substitution rate variation at human CpG sites correlates with non-CpG divergence, methylation level and GC content. Genome Biol. 12, R58 (2011).","journal-title":"Genome Biol."},{"key":"574_CR20","doi-asserted-by":"publisher","first-page":"436","DOI":"10.1038\/nature14539","volume":"521","author":"Y LeCun","year":"2015","unstructured":"LeCun, Y., Bengio, Y. & Hinton, G. Deep learning. Nature 521, 436\u2013444 (2015).","journal-title":"Nature"},{"key":"574_CR21","doi-asserted-by":"publisher","first-page":"389","DOI":"10.1038\/s41576-019-0122-6","volume":"20","author":"G Eraslan","year":"2019","unstructured":"Eraslan, G., Avsec, Z., Gagneur, J. & Theis, F. J. Deep learning: new computational modelling techniques for genomics. Nat. Rev. Genet. 20, 389\u2013403 (2019).","journal-title":"Nat. Rev. Genet."},{"key":"574_CR22","doi-asserted-by":"publisher","first-page":"1196","DOI":"10.1038\/s41592-021-01252-x","volume":"18","author":"Z Avsec","year":"2021","unstructured":"Avsec, Z. et al. Effective gene expression prediction from sequence by integrating long-range interactions. Nat. Methods 18, 1196\u20131203 (2021).","journal-title":"Nat. Methods"},{"key":"574_CR23","doi-asserted-by":"publisher","first-page":"931","DOI":"10.1038\/nmeth.3547","volume":"12","author":"J Zhou","year":"2015","unstructured":"Zhou, J. & Troyanskaya, O. G. Predicting effects of noncoding variants with deep learning-based sequence model. Nat. Methods 12, 931\u2013934 (2015).","journal-title":"Nat. Methods"},{"key":"574_CR24","doi-asserted-by":"publisher","first-page":"831","DOI":"10.1038\/nbt.3300","volume":"33","author":"B Alipanahi","year":"2015","unstructured":"Alipanahi, B., Delong, A., Weirauch, M. T. & Frey, B. J. Predicting the sequence specificities of DNA- and RNA-binding proteins by deep learning. Nat. Biotechnol. 33, 831\u2013838 (2015).","journal-title":"Nat. Biotechnol."},{"key":"574_CR25","doi-asserted-by":"publisher","first-page":"1118","DOI":"10.1038\/s41592-020-0960-3","volume":"17","author":"R Schwessinger","year":"2020","unstructured":"Schwessinger, R. et al. DeepC: predicting 3D genome folding using megabase-scale transfer learning. Nat. Methods 17, 1118\u20131124 (2020).","journal-title":"Nat. Methods"},{"key":"574_CR26","doi-asserted-by":"publisher","first-page":"535","DOI":"10.1016\/j.cell.2018.12.015","volume":"176","author":"K Jaganathan","year":"2019","unstructured":"Jaganathan, K. et al. Predicting splicing from primary sequence with deep learning. Cell 176, 535\u2013548 e524 (2019).","journal-title":"Cell"},{"key":"574_CR27","unstructured":"Kull, M. et al. Beyond temperature scaling: Obtaining well-calibrated multi-class probabilities with dirichlet calibration. In Advances in Neural Information Processing Systems 32 (NIPS, 2019)."},{"key":"574_CR28","doi-asserted-by":"publisher","first-page":"285","DOI":"10.1038\/nature19057","volume":"536","author":"M Lek","year":"2016","unstructured":"Lek, M. et al. Analysis of protein-coding genetic variation in 60,706 humans. Nature 536, 285\u2013291 (2016).","journal-title":"Nature"},{"key":"574_CR29","doi-asserted-by":"publisher","first-page":"331","DOI":"10.1038\/nature04406","volume":"439","author":"C Nusbaum","year":"2006","unstructured":"Nusbaum, C. et al. DNA sequence and analysis of human chromosome 8. Nature 439, 331\u2013335 (2006).","journal-title":"Nature"},{"key":"574_CR30","doi-asserted-by":"publisher","first-page":"487","DOI":"10.1038\/s41588-018-0071-6","volume":"50","author":"JM Goldmann","year":"2018","unstructured":"Goldmann, J. M. et al. Germline de novo mutation clusters arise during oocyte aging in genomic regions with high double-strand-break incidence. Nat. Genet. 50, 487\u2013492 (2018).","journal-title":"Nat. Genet."},{"key":"574_CR31","doi-asserted-by":"publisher","first-page":"eabc6617","DOI":"10.1126\/science.abc6617","volume":"370","author":"WC Warren","year":"2020","unstructured":"Warren, W. C. et al. Sequence diversity analyses of an improved rhesus macaque genome enhance its biomedical utility. Science 370, eabc6617 (2020).","journal-title":"Science"},{"key":"574_CR32","doi-asserted-by":"publisher","first-page":"e30","DOI":"10.1371\/journal.pgen.0020030","volume":"2","author":"MS Taylor","year":"2006","unstructured":"Taylor, M. S. et al. Heterotachy in mammalian promoter evolution. PLoS Genet. 2, e30 (2006).","journal-title":"PLoS Genet."},{"key":"574_CR33","doi-asserted-by":"publisher","first-page":"732","DOI":"10.1038\/s41586-022-04965-x","volume":"607","author":"BV Halldorsson","year":"2022","unstructured":"Halldorsson, B. V. et al. The sequences of 150,119 genomes in the UK Biobank. Nature 607, 732\u2013740 (2022).","journal-title":"Nature"},{"key":"574_CR34","doi-asserted-by":"publisher","first-page":"624","DOI":"10.1038\/217624a0","volume":"217","author":"M Kimura","year":"1968","unstructured":"Kimura, M. Evolutionary rate at the molecular level. Nature 217, 624\u2013626 (1968).","journal-title":"Nature"},{"key":"574_CR35","doi-asserted-by":"publisher","first-page":"333","DOI":"10.1038\/s41588-018-0062-7","volume":"50","author":"J di Iulio","year":"2018","unstructured":"di Iulio, J. et al. The human noncoding genome defined by genetic diversity. Nat. Genet. 50, 333\u2013337 (2018).","journal-title":"Nat. Genet."},{"key":"574_CR36","unstructured":"Ovadia, Y. et al. Can you trust your model\u2019s uncertainty? evaluating predictive uncertainty under dataset shift. In Advances in Neural Information Processing Systems 32 (NIPS, 2019)."},{"key":"574_CR37","doi-asserted-by":"publisher","first-page":"i269","DOI":"10.1093\/bioinformatics\/btz339","volume":"35","author":"A Trabelsi","year":"2019","unstructured":"Trabelsi, A., Chaabane, M. & Ben-Hur, A. Comprehensive evaluation of deep learning architectures for prediction of DNA\/RNA sequence binding specificities. Bioinformatics 35, i269\u2013i277 (2019).","journal-title":"Bioinformatics"},{"key":"574_CR38","doi-asserted-by":"crossref","unstructured":"He, K., Zhang, X., Ren, S. & Sun, J. Deep residual learning for image recognition. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition 770\u2013778 (IEEE, 2016).","DOI":"10.1109\/CVPR.2016.90"},{"key":"574_CR39","first-page":"8026","volume":"32","author":"A Paszke","year":"2019","unstructured":"Paszke, A. et al. Pytorch: an imperative style, high-performance deep learning library. Adv. Neural Inf. Process. Syst. 32, 8026\u20138037 (2019).","journal-title":"Adv. Neural Inf. Process. Syst."},{"key":"574_CR40","doi-asserted-by":"publisher","first-page":"3423","DOI":"10.1093\/bioinformatics\/btr539","volume":"27","author":"RK Dale","year":"2011","unstructured":"Dale, R. K., Pedersen, B. S. & Quinlan, A. R. Pybedtools: a flexible Python library for manipulating genomic datasets and annotations. Bioinformatics 27, 3423\u20133424 (2011).","journal-title":"Bioinformatics"},{"key":"574_CR41","doi-asserted-by":"publisher","DOI":"10.1038\/s41467-020-17155-y","volume":"11","author":"W Kopp","year":"2020","unstructured":"Kopp, W., Monti, R., Tamburrini, A., Ohler, U. & Akalin, A. Deep learning for genomics using Janggu. Nat. Commun. 11, 3488 (2020).","journal-title":"Nat. Commun."},{"key":"574_CR42","unstructured":"Kingma, D. P. & Ba, J. Adam: a method for stochastic optimization. In 3rd International Conference on Learning Representations (Eds. Bengio, Y. & LeCun, Y.) (ICLR, 2015)."},{"key":"574_CR43","unstructured":"Liaw, R. et al. Tune: a research platform for distributed model selection and training. Preprint at https:\/\/arxiv.org\/abs\/1807.05118 (2018)."},{"key":"574_CR44","doi-asserted-by":"publisher","first-page":"841","DOI":"10.1093\/bioinformatics\/btq033","volume":"26","author":"AR Quinlan","year":"2010","unstructured":"Quinlan, A. R. & Hall, I. M. BEDTools: a flexible suite of utilities for comparing genomic features. Bioinformatics 26, 841\u2013842 (2010).","journal-title":"Bioinformatics"},{"key":"574_CR45","doi-asserted-by":"publisher","first-page":"2156","DOI":"10.1093\/bioinformatics\/btr330","volume":"27","author":"P Danecek","year":"2011","unstructured":"Danecek, P. et al. The variant call format and VCFtools. Bioinformatics 27, 2156\u20132158 (2011).","journal-title":"Bioinformatics"},{"key":"574_CR46","first-page":"D913","volume":"48","author":"G Zhao","year":"2020","unstructured":"Zhao, G. et al. Gene4Denovo: an integrated database and analytic platform for de novo mutations in humans. Nucleic Acids Res. 48, D913\u2013D926 (2020).","journal-title":"Nucleic Acids Res."},{"key":"574_CR47","doi-asserted-by":"publisher","first-page":"519","DOI":"10.1038\/nature24018","volume":"549","author":"H Jonsson","year":"2017","unstructured":"Jonsson, H. et al. Parental influence on human germline de novo mutations in 1,548 trios from Iceland. Nature 549, 519\u2013522 (2017).","journal-title":"Nature"},{"key":"574_CR48","doi-asserted-by":"publisher","first-page":"602","DOI":"10.1038\/nn.4524","volume":"20","author":"R Yuen","year":"2017","unstructured":"Yuen, R. et al. Whole genome sequencing resource identifies 18 new candidate genes for autism spectrum disorder. Nat. Neurosci. 20, 602\u2013611 (2017).","journal-title":"Nat. Neurosci."},{"key":"574_CR49","doi-asserted-by":"publisher","first-page":"eaat6576","DOI":"10.1126\/science.aat6576","volume":"362","author":"JY An","year":"2018","unstructured":"An, J. Y. et al. Genome-wide de novo risk score implicates promoter variation in autism spectrum disorder. Science 362, eaat6576 (2018).","journal-title":"Science"},{"key":"574_CR50","doi-asserted-by":"publisher","DOI":"10.1038\/ncomms15183","volume":"8","author":"B Milholland","year":"2017","unstructured":"Milholland, B. et al. Differences between germline and somatic mutation rates in humans and mice. Nat. Commun. 8, 15183 (2017).","journal-title":"Nat. Commun."},{"key":"574_CR51","doi-asserted-by":"crossref","unstructured":"Vasimuddin, M., Misra, S., Li, H. & Aluru, S. Efficient architecture-aware acceleration of BWA-MEM for multicore systems. In 2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS) 314\u2013324 (IEEE, 2019).","DOI":"10.1109\/IPDPS.2019.00041"},{"key":"574_CR52","doi-asserted-by":"publisher","first-page":"481","DOI":"10.1016\/j.cell.2016.05.063","volume":"166","author":"TG Consortium","year":"2016","unstructured":"Consortium, T. G. 1,135 Genomes reveal the global pattern of polymorphism in Arabidopsis thaliana. Cell 166, 481\u2013491 (2016).","journal-title":"Cell"},{"key":"574_CR53","doi-asserted-by":"publisher","first-page":"1193","DOI":"10.1101\/gr.171546.113","volume":"24","author":"W Huang","year":"2014","unstructured":"Huang, W. et al. Natural variation in genome architecture among 205 Drosophila melanogaster genetic reference panel lines. Genome Res. 24, 1193\u20131208 (2014).","journal-title":"Genome Res."},{"key":"574_CR54","doi-asserted-by":"publisher","first-page":"538","DOI":"10.1038\/35046205","volume":"408","author":"F Lyko","year":"2000","unstructured":"Lyko, F., Ramsahoye, B. H. & Jaenisch, R. DNA methylation in Drosophila melanogaster. Nature 408, 538\u2013540 (2000).","journal-title":"Nature"},{"key":"574_CR55","doi-asserted-by":"publisher","first-page":"D766","DOI":"10.1093\/nar\/gky955","volume":"47","author":"A Frankish","year":"2019","unstructured":"Frankish, A. et al. GENCODE reference annotation for the human and mouse genomes. Nucleic Acids Res. 47, D766\u2013D773 (2019).","journal-title":"Nucleic Acids Res."},{"key":"574_CR56","doi-asserted-by":"publisher","first-page":"W160","DOI":"10.1093\/nar\/gkw257","volume":"44","author":"F Ramirez","year":"2016","unstructured":"Ramirez, F. et al. deepTools2: a next generation web server for deep-sequencing data analysis. Nucleic Acids Res. 44, W160\u2013W165 (2016).","journal-title":"Nucleic Acids Res."},{"key":"574_CR57","first-page":"100141","volume":"2","author":"T Wu","year":"2021","unstructured":"Wu, T. et al. clusterProfiler 4.0: a universal enrichment tool for interpreting omics data. Innovation 2, 100141 (2021).","journal-title":"Innovation"},{"key":"574_CR58","doi-asserted-by":"publisher","DOI":"10.1186\/s12864-020-6752-4","volume":"21","author":"A Berrio","year":"2020","unstructured":"Berrio, A., Haygood, R. & Wray, G. A. Identifying branch-specific positive selection throughout the regulatory genome using an appropriate proxy neutral. BMC Genomics 21, 359 (2020).","journal-title":"BMC Genomics"},{"key":"574_CR59","doi-asserted-by":"publisher","first-page":"173","DOI":"10.1038\/nature10811","volume":"482","author":"TF Mackay","year":"2012","unstructured":"Mackay, T. F. et al. The Drosophila melanogaster genetic reference panel. Nature 482, 173\u2013178 (2012).","journal-title":"Nature"},{"key":"574_CR60","doi-asserted-by":"publisher","first-page":"D862","DOI":"10.1093\/nar\/gkv1222","volume":"44","author":"MJ Landrum","year":"2016","unstructured":"Landrum, M. J. et al. ClinVar: public archive of interpretations of clinically relevant variants. Nucleic Acids Res. 44, D862\u2013D868 (2016).","journal-title":"Nucleic Acids Res."},{"key":"574_CR61","doi-asserted-by":"publisher","unstructured":"Fang, Y., Deng, S. & Li, C. Whole genome mutation rate maps for multiple species. Science Data Bank https:\/\/doi.org\/10.11922\/sciencedb.01173 (2022).","DOI":"10.11922\/sciencedb.01173"},{"key":"574_CR62","doi-asserted-by":"publisher","unstructured":"Fang, Y., Deng, S. & Li, C. Code MuRaL v1.0.0. Zenodo https:\/\/doi.org\/10.5281\/zenodo.6989025 (2022).","DOI":"10.5281\/zenodo.6989025"}],"container-title":["Nature Machine Intelligence"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.nature.com\/articles\/s42256-022-00574-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s42256-022-00574-5","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.nature.com\/articles\/s42256-022-00574-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,21]],"date-time":"2022-12-21T07:13:51Z","timestamp":1671606831000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.nature.com\/articles\/s42256-022-00574-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,12,8]]},"references-count":62,"journal-issue":{"issue":"12","published-online":{"date-parts":[[2022,12]]}},"alternative-id":["574"],"URL":"https:\/\/doi.org\/10.1038\/s42256-022-00574-5","relation":{"has-preprint":[{"id-type":"doi","id":"10.1101\/2021.10.25.465689","asserted-by":"object"}]},"ISSN":["2522-5839"],"issn-type":[{"value":"2522-5839","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,12,8]]},"assertion":[{"value":"15 December 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"25 October 2022","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"8 December 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"The authors declare no competing interests.","order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Competing interests"}}]}}