{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004723703,0.0002636733,0.000766702,0.0001627795,0.0002389221,0.00006589984,0.00004466467,0.0001561911,0.0000119072],"category_scores_gemma":[0.003304685,0.0002149169,0.0003943571,0.0002447525,0.00004857577,0.001402267,0.00003852178,0.0003002807,0.000002493896],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001890172,"about_ca_system_score_gemma":0.0002696753,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000195939,"about_ca_topic_score_gemma":0.0001328593,"domain_scores_codex":[0.9956809,0.000298652,0.001956766,0.0006809263,0.001087592,0.0002951804],"domain_scores_gemma":[0.9961215,0.001830449,0.0007785016,0.000411635,0.0007382448,0.0001196755],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001565323,0.00007293018,0.9264435,0.0002307888,0.0008517056,6.322968e-7,0.000188867,0.04889596,0.000004115484,0.0002331438,0.000005629866,0.02150747],"study_design_scores_gemma":[0.01471426,0.0002785656,0.9512371,0.000247276,0.0006792737,0.000002922035,0.0004211798,0.03192166,0.000004156258,0.0001243448,0.0001375191,0.0002316833],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9377549,0.00008974745,0.05826962,0.0001135013,0.0003162042,0.002655093,0.0007030076,0.00006745147,0.00003046465],"genre_scores_gemma":[0.9839593,0.0000531042,0.01062321,0.0001178754,0.0003158469,0.00002780062,0.004862665,0.00003555601,0.000004683759],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.04764641,"threshold_uncertainty_score":0.8764055,"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."}}