{"id":"W4400066345","doi":"10.1016/j.jcct.2024.05.028","title":"Evaluating The Accuracy Of A Fully Automated Artificial Intelligence-based Quantification Of Coronary Plaque Volume On CTCA","year":2024,"lang":"en","type":"article","venue":"Journal of cardiovascular computed tomography","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Medicine; Volume (thermodynamics); Radiology; Biomedical engineering; Cardiology; Internal 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":[0.002461439,0.000713859,0.0006718993,0.001332002,0.000247654,0.001528624,0.000808748,0.001666386,0.0008145901],"category_scores_gemma":[0.009654243,0.0003111841,0.0005669724,0.0004449369,0.000324893,0.0005487574,0.0006518051,0.0004163736,0.0003389578],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003458406,"about_ca_system_score_gemma":0.0004906504,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00399418,"about_ca_topic_score_gemma":0.003376618,"domain_scores_codex":[0.9985796,0.0005241716,0.0001061017,0.0003393826,0.0003573115,0.00009345353],"domain_scores_gemma":[0.9950323,0.00330481,0.0003087157,0.0003474496,0.000865864,0.0001407513],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00638175,0.0009642121,0.16793,0.0005001816,0.001624335,0.000366793,0.0002162078,0.2364249,0.05783404,0.001106288,0.00239697,0.5242544],"study_design_scores_gemma":[0.00005028903,0.0006339678,0.0461418,0.00002435851,0.0001908415,0.0002584355,0.00003236412,0.9438427,0.007902784,0.0004051772,0.0004792176,0.00003794944],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8843983,0.001850339,0.107882,0.0003132251,0.0001468724,0.0001166154,0.0008098688,0.001865932,0.002616964],"genre_scores_gemma":[0.9739336,0.00015753,0.02464646,0.00008944741,0.0000460967,0.0000287225,0.0005594096,0.00003768164,0.0005011008],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00399418,"threshold_uncertainty_score":0.01301748,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05504696446717367,"score_gpt":0.3413506450025424,"score_spread":0.2863036805353687,"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."}}