{"id":"W4410426946","doi":"10.1101/2025.05.14.25327536","title":"A multi-ancestry genetic reference for the Quebec population","year":2025,"lang":"en","type":"preprint","venue":"medRxiv","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mila - Quebec Artificial Intelligence Institute; McGill Genome Centre; Montreal Neurological Institute and Hospital; Genome Canada; HEC Montréal; Centre Hospitalier Universitaire Sainte-Justine; Centre Hospitalier de l’Université de Montréal; Université Laval; Université du Québec à Chicoutimi; Université de Montréal; McGill University and Génome Québec Innovation Centre; Cegep Edouard Montpetit; Montreal Heart Institute","funders":"Health Canada; Courtois Foundation; Fonds de Recherche du Québec - Santé; Partenariat Canadien Contre Le Cancer; Canadian Institutes of Health Research; Genome Canada; Alliance de recherche numérique du Canada; Natural Sciences and Engineering Research Council of Canada; Institut de Cardiologie de Montréal; Fondation Institut de Cardiologie de Montréal","keywords":"Population; Geography; Evolutionary biology; Genealogy; Genetic genealogy; Biology; Demography; History; Sociology","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":[0.001317885,0.0006938442,0.0005852473,0.003338858,0.003541551,0.001470004,0.001172034,0.0007724778,0.04563497],"category_scores_gemma":[0.004718656,0.0002525686,0.0004499562,0.005488301,0.0003733243,0.0003404625,0.0007296149,0.0009710889,0.006522147],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.007918544,"about_ca_system_score_gemma":0.01245338,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9498199,"about_ca_topic_score_gemma":0.9609929,"domain_scores_codex":[0.9992828,0.00009249189,0.00004467078,0.0002684993,0.0001996278,0.0001119309],"domain_scores_gemma":[0.9973694,0.0002261427,0.0001166617,0.0004939109,0.001641625,0.0001523158],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"observational","study_design_scores_codex":[0.0006098379,0.0001049924,0.07970654,0.0004653001,0.0003835174,0.001218377,0.001860554,0.001967099,0.006787003,0.01823404,0.6644779,0.2241849],"study_design_scores_gemma":[0.0001364276,0.00003342677,0.1793824,0.0004517859,0.0001242966,0.0009017267,0.0004115335,0.002123483,0.001353354,0.001636147,0.8133843,0.00006123144],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"dataset","genre_gemma":"empirical","genre_scores_codex":[0.09238042,0.006228064,0.04995983,0.003455638,0.001100092,0.0008663608,0.7257674,0.002660209,0.1175819],"genre_scores_gemma":[0.3424392,0.003253645,0.1020195,0.001688772,0.0002206949,0.001518863,0.4276867,0.001143479,0.1200291],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.05018008,"threshold_uncertainty_score":0.1526641,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05774748113719849,"score_gpt":0.3393016817801622,"score_spread":0.2815542006429638,"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."}}