{"id":"W4387934451","doi":"10.1016/j.jcjd.2023.10.305","title":"EVALUATION OF CHAT-BASED ARTIFICIAL INTELLIGENCE ALGORITHMS FOR PROVIDING ATRIAL FIBRILLATION RECOMMENDATIONS TO PATIENTS AND CLINICIANS","year":2023,"lang":"en","type":"article","venue":"Canadian Journal of Diabetes","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Atrial fibrillation; Medicine; Artificial intelligence; Machine learning; Computer science; Internal medicine","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"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":[0.006255818,0.001145195,0.001147203,0.001200048,0.0006815289,0.00160457,0.00165749,0.00205684,0.002956403],"category_scores_gemma":[0.03004288,0.0002981372,0.0005648941,0.0006761643,0.0003561338,0.00131402,0.001061729,0.001352439,0.0006792986],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001267674,"about_ca_system_score_gemma":0.001892836,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01306346,"about_ca_topic_score_gemma":0.00796635,"domain_scores_codex":[0.9974974,0.001229331,0.0003373466,0.0003429468,0.0004630313,0.0001299117],"domain_scores_gemma":[0.9603088,0.03300908,0.0007278699,0.0008157238,0.004141687,0.000996789],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0330577,0.01162935,0.06069468,0.001660854,0.001543566,0.0007801783,0.001172637,0.2337896,0.005688073,0.00207743,0.01427096,0.6336349],"study_design_scores_gemma":[0.0009160309,0.002757682,0.006139493,0.00008141499,0.000325619,0.0001869789,0.0002952298,0.9834086,0.003560032,0.0009716433,0.001318559,0.00003865923],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9287852,0.002135649,0.05345678,0.001530835,0.0005814647,0.0009731444,0.00131253,0.004958502,0.006265862],"genre_scores_gemma":[0.9342933,0.0004239935,0.06087651,0.000359437,0.000101277,0.0002853535,0.00164414,0.00005614348,0.001959986],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01306346,"threshold_uncertainty_score":0.03308433,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.334255850695632,"score_gpt":0.4613554335970898,"score_spread":0.1270995829014578,"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."}}