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A longer candidate (10.1016/j.copbio.2022.102853.64621) was visible in the surrounding text but could not be confirmed against doi.org as printed.","snippet":"Guo, T., and Li, X. (2023). Machine learning for predicting phenotype from genotype and644 environment. Current Opinion in Biotechnology79, 102853. URL:http://dx.doi.org/10.645 1016/j.copbio.2022.102853. doi:10.1016/j.copbio.2022.102853.646","arxiv_id":"2605.02954","detector":"doi_compliance","evidence":{"ref_index":10,"verdict_class":"incontrovertible","resolved_title":null,"printed_excerpt":"Guo, T., and Li, X. (2023). Machine learning for predicting phenotype from genotype and644 environment. Current Opinion in Biotechnology79, 102853. 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The cited work could not be located through any authoritative source.","snippet":"Chalmer, M.A., Esserlind, A.L., Olesen, J., and Hansen, T.F . (2018). Polygenic risk score:615 use in migraine research. J Headache Pain19, 29–10. doi:10.1186/s10194-018-0856-0.616","arxiv_id":"2605.02954","detector":"doi_compliance","evidence":{"doi":"10.1186/s10194-018-0856-0.616","arxiv_id":null,"ref_index":3,"raw_excerpt":"Chalmer, M.A., Esserlind, A.L., Olesen, J., and Hansen, T.F . (2018). Polygenic risk score:615 use in migraine research. 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