{"id":"W2932985964","doi":"10.1161/hcq.12.suppl_1.23","title":"Abstract 23: Patient Level Prediction Models Developed With Large Observational Databases Outperformed Existing Clinical Prediction Scores For Stratifying Bleeding Risk In Patients With Atrial Fibrillation","year":2019,"lang":"en","type":"article","venue":"Circulation Cardiovascular Quality and Outcomes","topic":"Clinical practice guidelines implementation","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"St. Clair College","funders":"","keywords":"Medicine; Observational study; Edoxaban; Dabigatran; Apixaban; Logistic regression; Atrial fibrillation; Rivaroxaban; Database; Internal medicine; Warfarin; Computer science","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":[0.01546546,0.001051878,0.0008494504,0.0007194816,0.0002694486,0.001662539,0.001040189,0.0007308302,0.002284128],"category_scores_gemma":[0.03305021,0.0003469345,0.001145773,0.0007037441,0.0002698756,0.001217377,0.0009827394,0.00128209,0.0005294477],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001106977,"about_ca_system_score_gemma":0.001661366,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01307897,"about_ca_topic_score_gemma":0.00604635,"domain_scores_codex":[0.9966698,0.00182142,0.0003133005,0.0007140369,0.0003560284,0.00012531],"domain_scores_gemma":[0.9786396,0.01618464,0.001490606,0.001109592,0.001995298,0.0005802614],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"observational","study_design_scores_codex":[0.003276511,0.001420632,0.4349311,0.0002837089,0.001685534,0.0002725235,0.0001887854,0.454755,0.001124139,0.001180918,0.007321466,0.09355961],"study_design_scores_gemma":[0.0001284451,0.0004356056,0.02116966,0.00001895657,0.0001277041,0.00005901483,0.00003220647,0.9763867,0.0005412092,0.0007107019,0.0003716483,0.00001804954],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9386202,0.0004292803,0.05009173,0.00133984,0.0001119786,0.0002269482,0.006229268,0.001294034,0.001656774],"genre_scores_gemma":[0.9831603,0.00008027197,0.01279134,0.0001440526,0.00002801859,0.00007746997,0.00334941,0.00002634537,0.000342711],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01546546,"threshold_uncertainty_score":0.08179009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.5295085476553695,"score_gpt":0.4686071907653125,"score_spread":0.06090135689005693,"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."}}