{"id":"W2106313946","doi":"10.1586/erd.11.31","title":"Determining patient prognosis using computed tomography coronary angiography","year":2011,"lang":"en","type":"review","venue":"Expert Review of Medical Devices","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital; University of Ottawa","funders":"Canadian Institutes of Health Research","keywords":"Medicine; Coronary artery disease; Stenosis; Computed tomography angiography; Radiology; Computed tomography; Angiography; Cardiology; Coronary angiography; Calcification; Internal medicine; Myocardial infarction","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0008177287,0.0007109183,0.004692089,0.000581124,0.0000722676,0.00001927653,0.0004969239,0.0004978193,0.0004144483],"category_scores_gemma":[0.0007625705,0.0004957137,0.004088736,0.001276055,0.0003398631,0.00007094028,0.0003067646,0.0006336379,0.00002263461],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004768745,"about_ca_system_score_gemma":0.0006593229,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00006815192,"about_ca_topic_score_gemma":0.000001163166,"domain_scores_codex":[0.9949869,0.0004115923,0.001911419,0.0006729474,0.001535261,0.000481864],"domain_scores_gemma":[0.9966427,0.0006786375,0.001012335,0.0007204887,0.0002746471,0.0006711574],"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":[0.000002588446,0.0002246186,0.001095503,0.1942646,0.0006972043,0.0002112883,0.00006162469,3.22981e-9,2.915621e-8,0.00000821732,0.005019234,0.7984151],"study_design_scores_gemma":[0.0001431152,0.0001295739,0.000113494,0.4323353,0.002613607,0.0005525816,0.00001252548,0.000006450442,6.699124e-7,7.06336e-7,0.5638285,0.0002634615],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000008318723,0.9964577,0.00008907954,0.0001237389,0.000924654,0.001709253,0.00003609127,0.0001128772,0.0005382854],"genre_scores_gemma":[0.00002944272,0.9906148,0.005148188,0.003138338,0.0004941403,0.0002068412,0.000273346,0.00009306877,0.00000183132],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.7981516,"threshold_uncertainty_score":0.9997494,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0579428039177697,"score_gpt":0.3819040098098833,"score_spread":0.3239612058921136,"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."}}