{"id":"W2073063260","doi":"10.1111/jth.12874","title":"Anemia predicts thromboembolic events, bleeding complications and mortality in patients with atrial fibrillation: insights from the RE‐LY trial","year":2015,"lang":"en","type":"article","venue":"Journal of Thrombosis and Haemostasis","topic":"Erythropoietin and Anemia Treatment","field":"Medicine","cited_by":78,"is_retracted":false,"has_abstract":false,"ca_institutions":"Hamilton Health Sciences; McMaster University; Population Health Research Institute","funders":"Daiichi Sankyo Europe; Janssen Biotech; Aegerion Pharmaceuticals; Regado Biosciences; Sanofi; Janssen Scientific Affairs; St. Jude Medical; Daiichi-Sankyo; Amgen; Pfizer; GlaxoSmithKline","keywords":"Medicine; Atrial fibrillation; Hazard ratio; Internal medicine; Anemia; Stroke (engine); Warfarin; Discontinuation; Myocardial infarction; Confidence interval; Proportional hazards model; Population; Cardiology","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":[0.000248008,0.0001669855,0.0005186878,0.00007160088,0.0001340302,0.00004538337,0.00007220358,0.00008889287,0.00001596178],"category_scores_gemma":[0.0000935221,0.00009417204,0.00009465071,0.0001653457,0.0001260177,0.0001921223,0.00004742598,0.0002008703,0.000001181686],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001062991,"about_ca_system_score_gemma":0.0001413408,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000274999,"about_ca_topic_score_gemma":0.0001112834,"domain_scores_codex":[0.998566,0.00009153011,0.0005221,0.0001895688,0.0004893126,0.0001415267],"domain_scores_gemma":[0.9989309,0.0001227794,0.0002929929,0.0002048914,0.0002305159,0.0002179383],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003143813,0.0001854783,0.9911268,0.00001617007,0.0003471936,0.000004316424,0.001662736,0.00003424759,0.00001332638,0.00004706861,0.001007837,0.002411039],"study_design_scores_gemma":[0.04737862,0.001433198,0.9482745,0.0003051122,0.0006563254,0.00001016875,0.0007311247,0.00003515649,0.00002779251,0.0004106027,0.0006391206,0.00009827741],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941705,0.001310794,0.00001196767,0.003556345,0.0001998251,0.000527024,0.00003183326,0.000008417132,0.0001832931],"genre_scores_gemma":[0.9971585,0.0009905767,0.001071777,0.0001841254,0.0005414295,0.000001773957,0.00003502676,0.00001385384,0.000002907319],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0442348,"threshold_uncertainty_score":0.3840224,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07775704806054762,"score_gpt":0.3264621589376229,"score_spread":0.2487051108770753,"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."}}