{"id":"W2288275057","doi":"10.1093/hmg/ddw055","title":"Testing the role of predicted gene knockouts in human anthropometric trait variation","year":2016,"lang":"en","type":"article","venue":"Human Molecular Genetics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"National Heart, Lung, and Blood Institute; Eunice Kennedy Shriver National Institute of Child Health and Human Development; European Regional Development Fund; Medical Research Council; Canada Research Chairs; National Institutes of Health; Fondation Institut de Cardiologie de Montréal; Génome Québec; National Institute for Health and Care Research; Genome Canada; National Institute of Diabetes and Digestive and Kidney Diseases; Li Ka Shing Foundation; National Center for Advancing Translational Sciences; Wellcome Trust; Canadian Institutes of Health Research; Andrea and Charles Bronfman Philanthropies; Wellcome; Tartu Ülikool","keywords":"Biology; Genetics; Biobank; Quantitative trait locus; Exome sequencing; Trait; Candidate gene; Anthropometry; Gene; Population; Genetic variation; Phenotype; Exome; Genotype; Demography; Internal medicine; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.01401303,0.000861824,0.0009340869,0.001224784,0.001058259,0.001016205,0.001273407,0.001304327,0.003946827],"category_scores_gemma":[0.03222033,0.0004433091,0.001715772,0.001771345,0.001849838,0.0007414829,0.001271774,0.001392325,0.0004272879],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003586751,"about_ca_system_score_gemma":0.0009291393,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005203426,"about_ca_topic_score_gemma":0.005673797,"domain_scores_codex":[0.9875826,0.006420946,0.0007568141,0.003836906,0.0008425328,0.0005601629],"domain_scores_gemma":[0.9727779,0.02255446,0.001603108,0.002279168,0.0003379706,0.0004474508],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.003482432,0.0002004197,0.8770482,0.000844877,0.005538892,0.002741827,0.0008894406,0.009142829,0.05200614,0.004858945,0.002146936,0.04109901],"study_design_scores_gemma":[0.0005732764,0.001233187,0.9060658,0.0002571605,0.004238083,0.004143107,0.0005062625,0.04199948,0.01832803,0.01124456,0.01128173,0.000129359],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8856862,0.001266467,0.102078,0.0008967285,0.0001596678,0.0001987017,0.006777983,0.0006585655,0.002277711],"genre_scores_gemma":[0.9737168,0.0002362892,0.02155493,0.0005917912,0.00003346187,0.0003328563,0.002795467,0.0002342526,0.0005041542],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01401303,"threshold_uncertainty_score":0.07410884,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01808572250672956,"score_gpt":0.2683353744122349,"score_spread":0.2502496519055054,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}