{"id":"W2926464126","doi":"10.1007/s00392-019-01473-3","title":"Body mass index and all-cause mortality in patients with atrial fibrillation: insights from the China atrial fibrillation registry study","year":2019,"lang":"en","type":"article","venue":"Clinical Research in Cardiology","topic":"Atrial Fibrillation Management and Outcomes","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Montréal; Montreal Heart Institute","funders":"National Key Research and Development Program of China; National Natural Science Foundation of China","keywords":"Medicine; Overweight; Underweight; Atrial fibrillation; Body mass index; Internal medicine; Obesity; Obesity paradox; Cardiology; Proportional hazards model; Mortality rate","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":[0.0013955,0.0006907936,0.001022526,0.001610078,0.0007463148,0.001109105,0.0007508178,0.000768528,0.0009428383],"category_scores_gemma":[0.0028856,0.0005308211,0.001128451,0.003493001,0.00032993,0.0009262846,0.001288274,0.001325791,0.0002208019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007579792,"about_ca_system_score_gemma":0.001539486,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02743419,"about_ca_topic_score_gemma":0.03974059,"domain_scores_codex":[0.9992841,0.0001750361,0.0001001528,0.0001492369,0.0001328351,0.0001586998],"domain_scores_gemma":[0.997831,0.0002498924,0.0007477289,0.0002918196,0.0003193665,0.0005600882],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001437059,0.0000472241,0.9977666,0.00001606509,0.0001752787,0.00005280805,0.00006340459,0.00004939924,0.00005211259,0.00003714008,0.0005272544,0.001069031],"study_design_scores_gemma":[0.00002121328,0.00002133935,0.999294,0.000007177748,0.000130764,0.00004422557,0.00009394124,0.0001652385,0.00001330071,0.00002860871,0.0001736904,0.000006468052],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9940389,0.001006603,0.00008669432,0.000306149,0.000025835,0.00002896683,0.003574719,0.000008862922,0.0009233674],"genre_scores_gemma":[0.9941896,0.0006043895,0.0001344588,0.00015542,0.00006084897,0.00005494133,0.004454055,0.000005137196,0.0003411614],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02743419,"threshold_uncertainty_score":0.05454904,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2009399905607813,"score_gpt":0.47569027996191,"score_spread":0.2747502894011287,"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."}}