{"id":"W3213819329","doi":"10.1016/j.xgen.2021.100029","title":"GA4GH: International policies and standards for data sharing across genomic research and healthcare","year":2021,"lang":"en","type":"article","venue":"Cell Genomics","topic":"Cancer Genomics and Diagnostics","field":"Biochemistry, Genetics and Molecular Biology","cited_by":294,"is_retracted":false,"has_abstract":true,"ca_institutions":"Indoc Research; Google (Canada); Vector Institute; University of Toronto; University Health Network; McGill University; Ontario Institute for Cancer Research; Canada's Michael Smith Genome Sciences Centre; University of Waterloo; Genome Canada; Ontario Genomics","funders":"Institute of Genetics; U.S. National Library of Medicine; National Cancer Institute; National Human Genome Research Institute; National Heart, Lung, and Blood Institute; Horizon 2020; Instituto de Salud Carlos III; Medical Research Council; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Health and Medical Research Council; Research Institute, Nationwide Children's Hospital; Compute Canada; Innovative Medicines Initiative; Novo Nordisk Fonden; Terry Fox Research Institute; Bayer Fund; Eidgenössische Technische Hochschule Zürich; Academy of Finland; Government of Ontario; National Taiwan University; Institut National de la Santé et de la Recherche Médicale; Microsoft; National University of Singapore; Institute for Research in Biomedicine; Government of Canada; Additional Ventures; National Center for Advancing Translational Sciences; Seventh Framework Programme; Swiss Institute of Bioinformatics; Invitae; International Business Machines Corporation; Canada Research Chairs; Cotton Research and Development Corporation; Virginia Marine Resources Commission; Google; EOSC-Life; Chan Zuckerberg Initiative; Wellcome Trust; Robertson Foundation; Novo Nordisk; Genome Canada; European Molecular Biology Laboratory; Canarie; Broad Institute; State Government of Victoria; Center for Individualized Medicine, Mayo Clinic; Deutsche Forschungsgemeinschaft; Japan Agency for Medical Research and Development; Novartis; Agency for Science, Technology and Research; Amazon Web Services; Howard Hughes Medical Institute; National Institute on Handicapped Research; Foundation Medicine; Mayo Clinic; Vanderbilt University; Intel Corporation; Staatssekretariat für Bildung, Forschung und Innovation; “la Caixa” Foundation; National Institutes of Health; Vanderbilt-Ingram Cancer Center; National Institute of General Medical Sciences; Ontario Genomics Institute; Canada Foundation for Innovation; Nationwide Children's Hospital","keywords":"Interoperability; Data sharing; Suite; Data science; Health care; Genomics; Big data; Key (lock); Alliance; Knowledge management; Computer science; Business; Genome; World Wide Web; Political science; Medicine; Computer security; Biology; Data mining","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006981887,0.00009939843,0.00011241,0.00002565989,0.0002073214,0.0001941845,0.0003618133,0.00009774806,0.000004339213],"category_scores_gemma":[0.0002085988,0.0001163361,0.00002071202,0.00003794626,0.0001189819,0.000004675756,0.00183552,0.00009416732,8.00439e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001022768,"about_ca_system_score_gemma":0.0004554551,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001166709,"about_ca_topic_score_gemma":0.0006817456,"domain_scores_codex":[0.9988226,0.00001430716,0.0001640245,0.0005665124,0.0001293085,0.0003032779],"domain_scores_gemma":[0.9987705,0.00005001215,0.00004051916,0.000582964,0.0004465299,0.0001095171],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003074857,0.00008764262,0.01486245,0.0002647509,0.0001072642,0.00001194818,0.001184183,0.00007574313,0.951592,0.00187703,0.01438955,0.01523996],"study_design_scores_gemma":[0.001143122,0.0002016156,0.002138259,0.00001554548,0.00001194533,0.00004561897,0.00142072,0.0009952815,0.08569872,0.001465816,0.9066057,0.0002576762],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9820451,0.01174311,0.0009861171,0.001022743,0.0002679748,0.0001801771,0.003257552,0.00000420974,0.0004929886],"genre_scores_gemma":[0.968106,0.02335057,0.004705371,0.0005776322,0.0008573977,0.00002107141,0.001545402,0.00004763503,0.0007888939],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8922161,"threshold_uncertainty_score":0.4744049,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1002161335346962,"score_gpt":0.4196946650027868,"score_spread":0.3194785314680906,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). 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