{"id":"W4405222949","doi":"10.1093/eurheartj/ehae826","title":"Focus on atrial fibrillation: role of atrioventricular node ablation, prediction by deep learning, and anticoagulation in device-detected arrhythmia","year":2024,"lang":"en","type":"article","venue":"European Heart Journal","topic":"Atrial Fibrillation Management and Outcomes","field":"Medicine","cited_by":5,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Daiichi Sankyo Europe; McMaster University; Amgen","keywords":"Medicine; Atrial fibrillation; Atrioventricular node; Cardiology; Ablation; Internal medicine; Cardiac arrhythmia; Focus (optics); Ablation of atrial fibrillation; Catheter ablation; Tachycardia","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.002896724,0.0006271609,0.001196271,0.0004003149,0.0002057238,0.002168618,0.0006355827,0.001013077,0.002994795],"category_scores_gemma":[0.01071165,0.0001813974,0.001117156,0.0003420727,0.0003419507,0.001820157,0.0006499708,0.002900979,0.0003741841],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004782943,"about_ca_system_score_gemma":0.0009318166,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002496348,"about_ca_topic_score_gemma":0.004849714,"domain_scores_codex":[0.9990877,0.0003348345,0.0001125672,0.0002456221,0.0001533076,0.0000660126],"domain_scores_gemma":[0.9915554,0.006108462,0.0007138217,0.0002859203,0.0008118785,0.0005245149],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.003713799,0.0006715292,0.4048445,0.001608788,0.003474847,0.0002554244,0.0001291315,0.004941158,0.001588124,0.002582717,0.013222,0.562968],"study_design_scores_gemma":[0.001395999,0.004660195,0.7663605,0.00823258,0.01326361,0.003054472,0.0007229063,0.1199432,0.003557075,0.03055203,0.04793975,0.0003177563],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5443195,0.3545818,0.01384261,0.05521849,0.004190419,0.00009074035,0.001422687,0.0001830992,0.02615084],"genre_scores_gemma":[0.9235692,0.05413952,0.005253403,0.006250179,0.007624973,0.00003671168,0.0009321296,0.00005127217,0.002142662],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002994795,"threshold_uncertainty_score":0.01531953,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02297851978209983,"score_gpt":0.2948928685569854,"score_spread":0.2719143487748856,"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."}}