{"id":"W3198964163","doi":"10.23958/ijirms/vol06-i09/1170","title":"Genetics - Predisposition and Application to Primary Preventions of CAD","year":2021,"lang":"en","type":"article","venue":"International Journal of Innovative Research in Medical Science","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Canadian Institutes of Health Research","keywords":"Coronary artery disease; Genetic predisposition; Medicine; Risk assessment; Internal medicine; Disease; Framingham Risk Score; CAD; Prospective cohort study; Bioinformatics; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002602503,0.0003112241,0.0004695137,0.001272789,0.0005031183,0.001314213,0.0004493482,0.001282082,0.003309573],"category_scores_gemma":[0.007667239,0.0001381765,0.0003131277,0.001078334,0.002000665,0.0007351594,0.0008194092,0.001535783,0.0006988255],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00104763,"about_ca_system_score_gemma":0.001921604,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003113368,"about_ca_topic_score_gemma":0.002729278,"domain_scores_codex":[0.9980039,0.001250987,0.00008207335,0.0001864822,0.0004016343,0.00007491208],"domain_scores_gemma":[0.9974497,0.001504444,0.000310617,0.0001521808,0.0003417239,0.0002413244],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.0003089997,0.0006057703,0.1606013,0.001801436,0.0003052815,0.001205833,0.001408073,0.001720265,0.002158786,0.09515212,0.02637188,0.7083603],"study_design_scores_gemma":[0.0000790109,0.001255476,0.3756282,0.003707862,0.0003695615,0.006840018,0.002194432,0.002074512,0.001908077,0.261658,0.3441738,0.0001110533],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.09067386,0.5883273,0.01469981,0.2181161,0.003942058,0.0001924681,0.0005295122,0.0001818819,0.08333696],"genre_scores_gemma":[0.6259775,0.3381102,0.01122831,0.01152662,0.004900923,0.000121954,0.0002058187,0.00002913996,0.007899448],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.003309573,"threshold_uncertainty_score":0.01376349,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03601708042250641,"score_gpt":0.4525917777755319,"score_spread":0.4165746973530255,"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."}}