{"id":"W2800582326","doi":"10.1016/j.ijcard.2018.02.101","title":"Functional CT assessment of extravascular contrast distribution volume and myocardial perfusion in acute myocardial infarction","year":2018,"lang":"en","type":"article","venue":"International Journal of Cardiology","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":11,"is_retracted":false,"has_abstract":false,"ca_institutions":"St Joseph's Health Care; London Health Sciences Centre; Lawson Health Research Institute; Robarts Clinical Trials","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research","keywords":"Medicine; Perfusion; Myocardial infarction; Magnetic resonance imaging; Edema; Ischemia; Cardiology; Myocardial perfusion imaging; Perfusion scanning; Nuclear medicine; Iodinated contrast; Internal medicine; Ex vivo; Radiology; In vivo; Computed tomography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.0005511351,0.0004805388,0.0002221764,0.001048477,0.0001635904,0.0006621662,0.0003633618,0.0006913768,0.001540068],"category_scores_gemma":[0.001733625,0.0002373364,0.0002275577,0.0003612288,0.0003565249,0.0007545294,0.0002926805,0.0004854139,0.0001566098],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002308723,"about_ca_system_score_gemma":0.0001820266,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001138479,"about_ca_topic_score_gemma":0.001103685,"domain_scores_codex":[0.9998717,0.00004454621,0.00001850469,0.0000130872,0.00001757154,0.00003456775],"domain_scores_gemma":[0.9995723,0.0001611913,0.00009567017,0.00002139335,0.00005492529,0.00009446779],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.008865036,0.0004993884,0.9026266,0.0001801133,0.0002354129,0.00677098,0.0002809393,0.001513857,0.04457863,0.0007542668,0.0004145786,0.03328021],"study_design_scores_gemma":[0.00005422498,0.000777,0.980413,0.00006188282,0.0001665788,0.006861259,0.0002673531,0.0060493,0.004411655,0.0004612896,0.0004534187,0.00002294686],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.996155,0.0009997662,0.0005504903,0.00007728758,0.000006988504,0.00001407545,0.00008962482,0.000007640883,0.002099176],"genre_scores_gemma":[0.9992154,0.0002252118,0.0002450582,0.00002054395,0.00001316996,0.000006315463,0.000068481,0.000002991224,0.0002028708],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001540068,"threshold_uncertainty_score":0.005152047,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00929456437382793,"score_gpt":0.2928113522929027,"score_spread":0.2835167879190748,"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."}}