{"id":"W4319777513","doi":"10.1002/gepi.22516","title":"A fast linkage method for population GWAS cohorts with related individuals","year":2023,"lang":"en","type":"article","venue":"Genetic Epidemiology","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"National Human Genome Research Institute; National Institute on Drug Abuse; National Institute on Aging; Norwegian Institute of Public Health; Medical School, University of Michigan; School of Public Health, University of Michigan; Helse Midt-Norge; Fakultet for medisin og helsevitenskap, Norges Teknisk-Naturvitenskapelige Universitet; Consiglio Nazionale delle Ricerche; Faculty of Medicine and Health, University of Sydney; Norges Teknisk-Naturvitenskapelige Universitet; Stiftelsen Kristian Gerhard Jebsen","keywords":"Genetics; Genotyping; Linkage (software); Population; Biology; Genetic linkage; Genome-wide association study; Genetic association; Computational biology; Single-nucleotide polymorphism; Gene; Medicine; Genotype","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.01083567,0.001533841,0.001596718,0.004570487,0.00180821,0.001583542,0.00288141,0.001358273,0.0158566],"category_scores_gemma":[0.02645541,0.001140365,0.002886512,0.004083308,0.0005884646,0.001234469,0.003010924,0.001919219,0.00559483],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006196739,"about_ca_system_score_gemma":0.002886081,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005117117,"about_ca_topic_score_gemma":0.005942909,"domain_scores_codex":[0.9953521,0.002265026,0.0002923572,0.0009768194,0.0009242235,0.0001894475],"domain_scores_gemma":[0.99406,0.002974502,0.0003828007,0.001522348,0.0009237533,0.0001367062],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0009793992,0.0002104211,0.02018387,0.0005926465,0.001917834,0.0008489643,0.0006821326,0.04007171,0.00779225,0.04735932,0.04853906,0.8308223],"study_design_scores_gemma":[0.001373566,0.0003996636,0.02228021,0.0002064627,0.0009184723,0.002884769,0.0002765468,0.6609547,0.01113406,0.131774,0.1674149,0.0003826703],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.004065077,0.0002942907,0.9885627,0.0001387806,0.0001273495,0.0001977265,0.001017838,0.005011959,0.0005841691],"genre_scores_gemma":[0.03416255,0.0002780442,0.9559413,0.0001573607,0.000128838,0.001614294,0.003487072,0.001378797,0.002851704],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.0158566,"threshold_uncertainty_score":0.05730522,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0265753600389996,"score_gpt":0.3377635907329521,"score_spread":0.3111882306939526,"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."}}