{"id":"W4411255293","doi":"10.1161/circep.124.013611","title":"Feasibility of Machine Learned Intracardiac Electrograms to Predict Postinfarction Ventricular Scar Topography","year":2025,"lang":"en","type":"article","venue":"Circulation Arrhythmia and Electrophysiology","topic":"Cardiac Arrhythmias and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"","keywords":"Medicine; Intracardiac injection; Cardiology; Internal medicine; Ventricular tachycardia","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001285076,0.0001992937,0.0005503573,0.0003296565,0.0001140934,0.00001099851,0.00003350935,0.0001516014,0.00002131126],"category_scores_gemma":[0.000103663,0.0001803602,0.0002757286,0.0007724768,0.00008910798,0.00005139562,0.00003498046,0.0001879363,0.000006079773],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000115182,"about_ca_system_score_gemma":0.00009888988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00007086611,"about_ca_topic_score_gemma":0.000003346941,"domain_scores_codex":[0.9985912,0.000109169,0.0003509219,0.0004629999,0.0001524514,0.0003332642],"domain_scores_gemma":[0.999182,0.00005876329,0.00009871567,0.0003417283,0.0001864301,0.0001322922],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003342928,0.0003137807,0.5499158,0.0002926043,0.001366131,0.00009533382,0.0001273696,0.001201019,0.2845558,0.004324321,0.0001831261,0.1542818],"study_design_scores_gemma":[0.001921753,0.0008410801,0.9875695,0.00005424691,0.0003706261,0.0001656449,0.00001366532,0.001010001,0.004346704,0.002180132,0.001370958,0.0001557501],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9942791,0.001219127,0.001921397,0.001051618,0.0001687295,0.000861338,0.00001278259,0.00007157604,0.000414343],"genre_scores_gemma":[0.9987415,0.0001910084,0.0003374616,0.0002926545,0.0001717581,0.0000508656,0.0001640469,0.000014277,0.00003639634],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4376536,"threshold_uncertainty_score":0.7354875,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0091800596093558,"score_gpt":0.2809721641858482,"score_spread":0.2717921045764924,"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."}}