{"id":"W4403204593","doi":"10.1016/j.jacadv.2024.101299","title":"New Frontiers for Predicting Atrial Fibrillation and Stroke","year":2024,"lang":"en","type":"editorial","venue":"JACC Advances","topic":"Atrial Fibrillation Management and Outcomes","field":"Medicine","cited_by":1,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Emory University","keywords":"Atrial fibrillation; Stroke (engine); Cardiology; Internal medicine; Medicine; Engineering","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":[0.0002127813,0.0002688037,0.0005914733,0.0002058025,0.00009560975,0.0001109092,0.0000588862,0.0003864956,0.00002457597],"category_scores_gemma":[0.001274141,0.0002303244,0.0003606068,0.00011362,0.00002685238,0.0002599995,0.00006525229,0.0002310436,0.00001066972],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008212916,"about_ca_system_score_gemma":0.0002026303,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000014023,"about_ca_topic_score_gemma":0.000008408794,"domain_scores_codex":[0.9983934,0.00001590433,0.0004064839,0.0004688866,0.0004872137,0.0002281465],"domain_scores_gemma":[0.9986905,0.0007062238,0.0002263053,0.0001617095,0.00009798863,0.0001172008],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006614966,2.129948e-7,0.005824026,0.00060751,0.000246659,0.000002058205,0.0000531018,0.0000616883,0.000004305832,0.00005671428,0.9077043,0.08477795],"study_design_scores_gemma":[0.001926871,0.000222366,0.0001170812,0.0002185032,0.000957173,7.18709e-7,0.00009497577,0.0006438116,0.000008763016,0.001804139,0.9938004,0.0002052062],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"editorial","genre_gemma":"editorial","genre_scores_codex":[0.0001038127,0.03532642,0.0115947,0.001072309,0.9493995,0.001216357,0.000199624,0.0002176011,0.0008696786],"genre_scores_gemma":[0.00004478491,0.003683824,0.0189695,0.000009265693,0.9273906,0.000001813851,0.0005605425,0.00005860369,0.049281],"genre_candidate":"editorial","genre_consensus":"editorial","teacher_disagreement_score":0.08609612,"threshold_uncertainty_score":0.9392356,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02064858292737118,"score_gpt":0.3375423725396575,"score_spread":0.3168937896122863,"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."}}