{"id":"W4404905344","doi":"10.1016/j.cjca.2024.11.029","title":"Pediatric Cardiology Machine Learning: Clinical Integration and Ethics","year":2024,"lang":"en","type":"letter","venue":"Canadian Journal of Cardiology","topic":"Artificial Intelligence in Healthcare and Education","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Medicine; Relevance (law); Perspective (graphical); Engineering ethics; Subject (documents); Precision medicine; Intensive care medicine; Medical education; Artificial intelligence; Pathology; Library science","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":[0.01021105,0.0005484489,0.001476566,0.0008492214,0.005782804,0.008559763,0.001725573,0.07608099,0.00710256],"category_scores_gemma":[0.0777733,0.0007912431,0.001098515,0.0007431361,0.009919756,0.004750315,0.003120694,0.06501403,0.003708111],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.009125733,"about_ca_system_score_gemma":0.01739533,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01695857,"about_ca_topic_score_gemma":0.05202592,"domain_scores_codex":[0.9877048,0.004745295,0.001386996,0.001125479,0.003513547,0.001523848],"domain_scores_gemma":[0.9186491,0.05496725,0.002822818,0.00155857,0.01009825,0.01190407],"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":[0.00001766862,0.00002814233,0.001320481,0.00003694022,0.00001663123,0.001712839,0.0002487931,0.0001360867,0.00008090436,0.02525169,0.956962,0.01418783],"study_design_scores_gemma":[0.00008940463,0.00005332174,0.002714553,0.0006751146,0.00002960782,0.005522424,0.0009529012,0.00229886,0.0002140435,0.1061658,0.8811885,0.00009547255],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.0001511532,0.0003585498,0.0001033503,0.9953665,0.002246669,0.000002064257,0.000007302879,0.000003876148,0.001760539],"genre_scores_gemma":[0.01051249,0.00126789,0.0007486059,0.9357416,0.04286286,0.00002996816,0.00001760246,0.0000236422,0.008795321],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.07608099,"threshold_uncertainty_score":0.06621218,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2573769241554372,"score_gpt":0.4514138905941956,"score_spread":0.1940369664387584,"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."}}