{"id":"W4381158111","doi":"10.1161/circep.123.012015","title":"Evaluating Recommendations About Atrial Fibrillation for Patients and Clinicians Obtained From Chat-Based Artificial Intelligence Algorithms","year":2023,"lang":"en","type":"article","venue":"Circulation Arrhythmia and Electrophysiology","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"McGill University","funders":"National Institute of Allergy and Infectious Diseases; National Cancer Institute; National Heart, Lung, and Blood Institute","keywords":"Atrial fibrillation; Computer science; Algorithm; Artificial intelligence; Internal medicine; Cardiology; Medicine","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":[0.009232833,0.0009933823,0.001211763,0.002833836,0.0005560592,0.001831035,0.0009752287,0.002782603,0.002931673],"category_scores_gemma":[0.06442969,0.0002542129,0.001010439,0.001257837,0.0002541186,0.001247487,0.0007226122,0.001194538,0.0007858351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000832367,"about_ca_system_score_gemma":0.001188449,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008103432,"about_ca_topic_score_gemma":0.00862985,"domain_scores_codex":[0.9946002,0.002851545,0.0007536232,0.0006135239,0.00096932,0.0002118394],"domain_scores_gemma":[0.8957302,0.0940839,0.001997355,0.001324961,0.005440883,0.001422842],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.02013718,0.004939585,0.5682052,0.001406337,0.004499462,0.0008291295,0.0009041388,0.09432656,0.002319111,0.0008212858,0.009838662,0.2917733],"study_design_scores_gemma":[0.001673203,0.004981611,0.1239758,0.0004222169,0.002984378,0.0005790576,0.0009959255,0.8550571,0.004017904,0.002520188,0.002671179,0.0001213298],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9769741,0.002088723,0.0126502,0.001392061,0.0002620678,0.0004002339,0.002472838,0.0005160843,0.003243726],"genre_scores_gemma":[0.9806635,0.0003581679,0.01484386,0.0002740875,0.0001302158,0.0001102131,0.00300078,0.00001500552,0.0006042916],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009232833,"threshold_uncertainty_score":0.04882848,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06686403774468935,"score_gpt":0.3798991685831871,"score_spread":0.3130351308384977,"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."}}