{"id":"W2514155774","doi":"10.71781/1059","title":"The French Canadian founder population : lessons and insights for genetic epidemiological research","year":2015,"lang":"en","type":"dissertation","venue":"Papyrus : Institutional Repository (Université de Montréal)","topic":"Race, Genetics, and Society","field":"Biochemistry, Genetics and Molecular Biology","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research; Partenariat Canadien Contre Le Cancer; Génome Québec","keywords":"Founder effect; Genetic epidemiology; Genealogy; Epidemiology; Population; Biology; Genetics; History; Medicine; Demography; Sociology; Genotype; Haplotype; Gene","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["sts"],"consensus_categories":[],"category_scores_codex":[0.0005064509,0.0002198927,0.000202074,0.00009200322,0.007493625,0.00005926099,0.000279773,0.0006502465,0.000001683458],"category_scores_gemma":[0.000298738,0.0001917258,0.0001472594,0.00009358154,0.0002692546,0.00000748193,0.00007736954,0.00026645,0.000002962045],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001266071,"about_ca_system_score_gemma":0.001981449,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.1594255,"about_ca_topic_score_gemma":0.6713018,"domain_scores_codex":[0.99832,0.0001916455,0.0002321475,0.0005275074,0.0003072614,0.0004214624],"domain_scores_gemma":[0.9985517,0.0001071969,0.0001256392,0.0003436788,0.0005181484,0.0003536023],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004886324,0.0006843911,0.1299275,0.001003152,0.004432573,0.0008693564,0.118089,0.008069554,0.1618313,0.07883235,0.3565764,0.1347981],"study_design_scores_gemma":[0.001069602,0.0004050494,0.4058876,0.00006620766,0.0001708981,0.000137986,0.02670535,0.0009026322,0.00174566,0.01529935,0.5469108,0.0006989291],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.950317,0.04179916,0.0000585016,0.0004496445,0.0007165881,0.0005087305,0.00004796184,0.00001130793,0.006091083],"genre_scores_gemma":[0.9559553,0.003165778,0.000641291,0.0000707258,0.0003405547,0.00006491425,0.001450949,0.00002442512,0.03828602],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5118763,"threshold_uncertainty_score":0.9937985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02456795652397347,"score_gpt":0.2660120012593343,"score_spread":0.2414440447353609,"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."}}