{"id":"W4220691247","doi":"10.1136/bmjopen-2021-059021","title":"Cohort profile: genomic data for 26 622 individuals from the Canadian Longitudinal Study on Aging (CLSA)","year":2022,"lang":"en","type":"article","venue":"BMJ Open","topic":"Glaucoma and retinal disorders","field":"Medicine","cited_by":81,"is_retracted":false,"has_abstract":true,"ca_institutions":"Dalhousie University; Impact; University of Toronto; Hospital for Sick Children; Université de Montréal; Hamilton Regional Laboratory Medicine Program; Montreal Heart Institute; McMaster University; Public Health Ontario; St. Joseph’s Healthcare Hamilton; Jewish General Hospital; McGill University; McGill Genome Centre","funders":"Canadian Institutes of Health Research; Canada Foundation for Innovation; Government of Canada; Newfoundland and Labrador; Genome Canada","keywords":"Medicine; Genotyping; Cohort; Psychosocial; Disease; Genetics; Genotype; Bioinformatics; Gene; Internal medicine; Biology; Psychiatry","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":[0.001758493,0.0007749463,0.0007895559,0.003164673,0.002497973,0.001050145,0.001526144,0.0006725088,0.004788243],"category_scores_gemma":[0.00550514,0.0004142567,0.0008609298,0.006720818,0.0003448803,0.0002746581,0.00119754,0.0008263332,0.001506869],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.004898204,"about_ca_system_score_gemma":0.01274264,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.8950616,"about_ca_topic_score_gemma":0.9345686,"domain_scores_codex":[0.9986125,0.0001086832,0.0001382586,0.0003428235,0.000575911,0.0002218313],"domain_scores_gemma":[0.9955145,0.0002275551,0.0004558899,0.0008369399,0.002469599,0.00049551],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0009976359,0.0001210596,0.8504867,0.0005628559,0.001026868,0.0004760358,0.0007714931,0.0008360398,0.002073129,0.001057115,0.1138153,0.02777594],"study_design_scores_gemma":[0.0001225925,0.00005915817,0.9506302,0.0001401435,0.0002244518,0.0002914837,0.00032138,0.0003320294,0.0003580051,0.0002235401,0.04724686,0.00005006096],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"dataset","genre_gemma":"dataset","genre_scores_codex":[0.2136971,0.001104994,0.002189378,0.000457056,0.00005834117,0.00049781,0.7775208,0.0001634709,0.004311113],"genre_scores_gemma":[0.246139,0.0009407567,0.005500644,0.0005623904,0.00005087793,0.001057183,0.7406071,0.00007942515,0.005062636],"genre_candidate":"dataset","genre_consensus":"dataset","teacher_disagreement_score":0.1049384,"threshold_uncertainty_score":0.2111127,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2055501161924478,"score_gpt":0.4298393303833276,"score_spread":0.2242892141908799,"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."}}