{"id":"W2235463930","doi":"10.1503/cmaj.150071","title":"Coronary computed tomography angiography","year":2015,"lang":"en","type":"article","venue":"Canadian Medical Association Journal","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; St. Paul's Hospital; University of British Columbia Hospital","funders":"","keywords":"Coronary angiography; Medicine; Contrast (vision); Image quality; Radiology; Angiography; Computed tomography; Computed tomography angiography; Contrast medium; Heart rate; Tomography; Nuclear medicine; Computer science; Cardiology; Artificial intelligence; Image (mathematics); Blood pressure; Myocardial infarction","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.0005777777,0.001238755,0.001899277,0.002624271,0.0009948532,0.0007642615,0.0007249453,0.001745196,0.02177875],"category_scores_gemma":[0.001478896,0.0003480714,0.0006150699,0.001835157,0.0004546991,0.0004919103,0.0003931573,0.00167638,0.005938457],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007618034,"about_ca_system_score_gemma":0.001315078,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006004483,"about_ca_topic_score_gemma":0.007423797,"domain_scores_codex":[0.9995303,0.00005180778,0.00003418334,0.0001157155,0.0001529264,0.000115117],"domain_scores_gemma":[0.9994086,0.00007184066,0.00004334586,0.00007930574,0.0002517535,0.0001451783],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.004919594,0.002247976,0.1599677,0.002185622,0.00126972,0.2101779,0.0005191359,0.001758746,0.05789899,0.008651547,0.1631905,0.3872125],"study_design_scores_gemma":[0.001334702,0.002529811,0.2899149,0.00291118,0.00102846,0.4036053,0.0003443812,0.005238411,0.01244172,0.007392682,0.2729146,0.0003438404],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.2355371,0.085873,0.04760035,0.0168556,0.002917232,0.004738498,0.01736726,0.003654336,0.5854567],"genre_scores_gemma":[0.8072814,0.0383559,0.02444435,0.02304638,0.005052516,0.001631701,0.0166566,0.0004752911,0.08305582],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.02177875,"threshold_uncertainty_score":0.0728572,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00979410612480023,"score_gpt":0.240009285979531,"score_spread":0.2302151798547308,"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."}}