{"id":"W2173487411","doi":"10.1016/j.jcmg.2015.08.006","title":"Noninvasive Fractional Flow Reserve Derived From Coronary CT Angiography","year":2015,"lang":"en","type":"review","venue":"JACC. Cardiovascular imaging","topic":"Coronary Interventions and Diagnostics","field":"Medicine","cited_by":258,"is_retracted":false,"has_abstract":false,"ca_institutions":"St. Paul's Hospital; University of British Columbia","funders":"GE Healthcare; Cardiovascular Research Foundation","keywords":"Fractional flow reserve; Medicine; Stenosis; Radiology; Hemodynamics; Angiography; Coronary angiography; Cardiology; Computed tomography; Coronary artery disease; Internal medicine; Computed tomography angiography; Myocardial infarction","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":["metaepi_narrow","metaepi_broad"],"consensus_categories":[],"category_scores_codex":[0.0007330971,0.0007937102,0.003340539,0.0006848418,0.0001816926,0.0001237577,0.0003786537,0.0001990304,0.0005789238],"category_scores_gemma":[0.0003722132,0.0007231911,0.01513682,0.0007039108,0.0001449409,0.0002644903,0.0003529304,0.0009446943,0.0004203583],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004622205,"about_ca_system_score_gemma":0.0008060011,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0006631425,"about_ca_topic_score_gemma":0.0000185461,"domain_scores_codex":[0.995743,0.0004477217,0.0009344683,0.001072851,0.0012352,0.0005666967],"domain_scores_gemma":[0.9963579,0.0004657388,0.0003079899,0.001835961,0.0005861346,0.0004463432],"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":[0.00002429843,0.000191169,0.001472105,0.002766,0.01563482,0.009225173,0.00002975434,0.00005289852,2.078025e-7,0.00000475498,0.01430116,0.9562976],"study_design_scores_gemma":[0.001418144,0.00005924127,0.001351686,0.01338735,0.02181471,0.005521883,0.0001150469,0.000126812,0.000001352792,0.00007389698,0.9554762,0.0006537081],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00006861638,0.9917773,0.002537363,0.00006548453,0.001305314,0.001329609,0.0008803947,0.0001868148,0.00184911],"genre_scores_gemma":[0.000340029,0.9882505,0.003631119,0.0001063562,0.001557309,0.0002965756,0.005464808,0.0001945722,0.0001587077],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.955644,"threshold_uncertainty_score":0.9995219,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04927072337380496,"score_gpt":0.3224063539142654,"score_spread":0.2731356305404605,"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."}}