{"id":"W3210824720","doi":"10.21203/rs.3.rs-958135/v1","title":"Comparison of State-Of-The-Art Neural Network Survival Models With The Pooled Cohort Equations for Cardiovascular Disease Risk Prediction","year":2021,"lang":"en","type":"preprint","venue":"Research Square","topic":"Artificial Intelligence in Healthcare","field":"Health Professions","cited_by":2,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Manitoba","funders":"U.S. National Library of Medicine; National Institutes of Health","keywords":"Proportional hazards model; Pooling; Cohort; Survival analysis; Artificial neural network; Medicine; Computer science; Statistics; Artificial intelligence; Internal medicine; Mathematics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"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":[0.02019398,0.001457529,0.002435215,0.001125255,0.00047815,0.00170518,0.002382012,0.001752371,0.002787081],"category_scores_gemma":[0.02555481,0.0005700899,0.002756389,0.001041289,0.0003838119,0.001769071,0.001205339,0.002758037,0.0008102479],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001152115,"about_ca_system_score_gemma":0.002117793,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.03422154,"about_ca_topic_score_gemma":0.02335822,"domain_scores_codex":[0.9970624,0.001823357,0.0002277528,0.0005145542,0.0002431262,0.0001288719],"domain_scores_gemma":[0.9784811,0.01753764,0.0005180803,0.001480683,0.001698,0.0002844991],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.01245337,0.00100748,0.08282723,0.0009538574,0.009647023,0.0001736691,0.0003210367,0.6551152,0.000803804,0.00387502,0.01146404,0.2213583],"study_design_scores_gemma":[0.0002532662,0.0004359229,0.01520042,0.0001217535,0.001045232,0.00004534258,0.00007069726,0.979229,0.0003670776,0.002257745,0.0009175076,0.00005604884],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8331518,0.01896871,0.1296257,0.002884264,0.001256086,0.0002022493,0.008677348,0.001369325,0.003864522],"genre_scores_gemma":[0.9574215,0.003077862,0.02700797,0.0003748002,0.0003350704,0.0001690364,0.008534059,0.0001860333,0.002893732],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03422154,"threshold_uncertainty_score":0.1067972,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.310725653595216,"score_gpt":0.5205198769652457,"score_spread":0.2097942233700297,"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."}}