{"id":"W7133000466","doi":"","title":"Updating and Developing Risk Prediction Models for Incident Cardiovascular Disease in Ontario, Canada","year":2023,"lang":"","type":"dissertation","venue":"TSpace","topic":"Acute Myocardial Infarction Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Health Services and Policy Research","funders":"Canadian Institutes of Health Research; Department of Medicine, University of Toronto; University of Toronto; Heart and Stroke Foundation of Canada","keywords":"Framingham Risk Score; Cohort; Disease; Atherosclerotic cardiovascular disease; Risk assessment; Framingham Heart Study; Cohort study; Predictive modelling","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":[0.005189149,0.0006904287,0.0005730682,0.001606702,0.002443372,0.002237709,0.002057396,0.0004776148,0.001731076],"category_scores_gemma":[0.01530299,0.0006836822,0.0009158624,0.002128472,0.0004994132,0.0007453986,0.001082939,0.000780263,0.0005464426],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.04486983,"about_ca_system_score_gemma":0.07279415,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.9957153,"about_ca_topic_score_gemma":0.9953951,"domain_scores_codex":[0.9981465,0.0004061896,0.0001546365,0.0002957046,0.0007359448,0.0002609071],"domain_scores_gemma":[0.9930639,0.001088964,0.0004080777,0.0002411839,0.004882605,0.0003153807],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003991559,0.0002713077,0.5824441,0.0003331377,0.0004093677,0.0004398285,0.001756389,0.1989152,0.001103865,0.004404256,0.02855386,0.1809696],"study_design_scores_gemma":[0.0001366444,0.00009330986,0.2072996,0.0002037383,0.0002885459,0.00009615696,0.001194911,0.766699,0.001070777,0.001871063,0.02091805,0.0001282606],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8720263,0.002463702,0.07692809,0.004874001,0.0002886376,0.001358952,0.01767541,0.001639611,0.02274526],"genre_scores_gemma":[0.9008753,0.001965941,0.07912984,0.0003273927,0.00003675584,0.000302485,0.008073064,0.0001764131,0.009112772],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04486983,"threshold_uncertainty_score":0.3255549,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04024293088700156,"score_gpt":0.3251128862197847,"score_spread":0.2848699553327831,"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."}}