{"id":"W4399302972","doi":"10.1016/j.cjca.2024.05.027","title":"Role of Artificial Intelligence in Improving Syncope Management","year":2024,"lang":"en","type":"review","venue":"Canadian Journal of Cardiology","topic":"Cardiovascular Syncope and Autonomic Disorders","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University Health Centre; McGill University; University of Calgary; Ottawa Hospital; Jewish General Hospital; Libin Cardiovascular Institute of Alberta; University of Ottawa","funders":"National Institutes of Health; National Heart, Lung, and Blood Institute; Physicians' Services Incorporated Foundation","keywords":"Medicine; Syncope (phonology); Artificial intelligence; Cardiology","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"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":[0.01369357,0.001095044,0.001150851,0.003065931,0.0007877572,0.006560808,0.002112515,0.003361,0.00421484],"category_scores_gemma":[0.03918313,0.0003172238,0.0008143022,0.001829464,0.003045319,0.006141511,0.002911875,0.004984613,0.001477237],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001903823,"about_ca_system_score_gemma":0.002937849,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002073365,"about_ca_topic_score_gemma":0.001273741,"domain_scores_codex":[0.9925328,0.004025508,0.0004721837,0.0006187468,0.00209331,0.0002574325],"domain_scores_gemma":[0.9748484,0.01784137,0.001243451,0.001146027,0.003941701,0.0009789956],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001642356,0.0003443382,0.007036603,0.00218545,0.0004038015,0.0003000445,0.0006146838,0.013973,0.0008529859,0.1137167,0.0651584,0.7952497],"study_design_scores_gemma":[0.00009499358,0.0004036432,0.007717634,0.005469903,0.0002521944,0.0005130204,0.001247689,0.05819737,0.001665125,0.5338938,0.3903648,0.000179787],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.01387949,0.4016819,0.157701,0.3165683,0.005779328,0.000317075,0.0004992016,0.001581845,0.1019918],"genre_scores_gemma":[0.4066506,0.3223656,0.2132933,0.03904284,0.008340733,0.0004221624,0.0008435944,0.0002787847,0.008762367],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.01369357,"threshold_uncertainty_score":0.0724194,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02357686542243891,"score_gpt":0.286391943724066,"score_spread":0.2628150783016271,"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."}}