{"id":"W4415349988","doi":"10.1016/j.cjca.2025.08.203","title":"“A Responsible Framework for Applying Artificial Intelligence on Medical Images and Signals at the Point of Care: The PACS-AI Platform [Canadian Journal of Cardiology Volume 40, Issue 10, October 2024, Pages 1828-1840]”","year":2025,"lang":"en","type":"erratum","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":"Polytechnique Montréal; Mila - Quebec Artificial Intelligence Institute; Université de Montréal; Université Laval; Montreal Heart Institute; University of Ottawa","funders":"Fonds de recherche du Québec – Nature et technologies; Natural Sciences and Engineering Research Council of Canada; Fondation Institut de Cardiologie de Montréal; Institut de Valorisation des Données; Radiological Society of North America; Institut de Cardiologie de Montréal; National Institutes of Health; Canadian Institute for Advanced Research; National Institute of Biomedical Imaging and Bioengineering; Gordon and Betty Moore Foundation; Fonds de Recherche du Québec - Santé; Robert Wood Johnson Foundation","keywords":"Volume (thermodynamics); Point (geometry); Ventricular volume","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"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":[0.01686675,0.001395336,0.0008400189,0.002384661,0.00259575,0.009875429,0.00524164,0.008567252,0.02242775],"category_scores_gemma":[0.03709243,0.0012377,0.0009894058,0.001460999,0.0051297,0.009048802,0.006043136,0.005941241,0.02356463],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003185377,"about_ca_system_score_gemma":0.01554514,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01987072,"about_ca_topic_score_gemma":0.02848933,"domain_scores_codex":[0.9857985,0.003724721,0.001369757,0.0009181078,0.007538732,0.0006501642],"domain_scores_gemma":[0.9790273,0.005735738,0.00068125,0.003246616,0.009966253,0.001342871],"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":[0.00007286065,0.00003649277,0.0002733674,0.000170768,0.00002136173,0.0004227177,0.0002749418,0.001133256,0.001045721,0.1582221,0.7556987,0.08262767],"study_design_scores_gemma":[0.0000228395,0.00001704748,0.0002385734,0.0001291947,0.00001078434,0.0002856208,0.00008097638,0.004842993,0.0016716,0.03342428,0.959228,0.00004826171],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"other","genre_scores_codex":[0.001319106,0.004394342,0.6341125,0.1477195,0.05236165,0.0007895067,0.00277243,0.02199842,0.1345325],"genre_scores_gemma":[0.02362776,0.005304435,0.6763111,0.0405508,0.01186894,0.0008171101,0.00573189,0.005164541,0.2306234],"genre_candidate":"other","genre_consensus":null,"teacher_disagreement_score":0.02242775,"threshold_uncertainty_score":0.08920103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.082675634680114,"score_gpt":0.3802099460929746,"score_spread":0.2975343114128606,"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."}}