{"id":"W2770342819","doi":"10.1148/radiol.2017162620","title":"Fractional Flow Reserve Estimated at Coronary CT Angiography in Intermediate Lesions: Comparison of Diagnostic Accuracy of Different Methods to Determine Coronary Flow Distribution","year":2017,"lang":"en","type":"article","venue":"Radiology","topic":"Coronary Interventions and Diagnostics","field":"Medicine","cited_by":41,"is_retracted":false,"has_abstract":true,"ca_institutions":"Ottawa Hospital","funders":"National Institute of Biomedical Imaging and Bioengineering; Toshiba Medical Systems","keywords":"Medicine; Fractional flow reserve; Coronary angiography; Radiology; Diagnostic accuracy; Coronary flow reserve; Distribution (mathematics); Cardiology; Angiography; Nuclear medicine; Internal medicine; Blood flow; Myocardial infarction; Mathematical analysis","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":[0.003834086,0.0005674558,0.0004907409,0.001934541,0.0001711696,0.0006633695,0.0003892827,0.000627264,0.0003873066],"category_scores_gemma":[0.01003312,0.0002361083,0.0004440378,0.0003430782,0.0003705997,0.0005539163,0.0003766,0.0003680428,0.0001798039],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000247826,"about_ca_system_score_gemma":0.0001616732,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004822639,"about_ca_topic_score_gemma":0.0007374539,"domain_scores_codex":[0.9988604,0.0004303616,0.0001434203,0.0002290744,0.0002484659,0.00008833238],"domain_scores_gemma":[0.9948406,0.002751815,0.001133092,0.0003724262,0.0005528441,0.0003492173],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001134472,0.00005837261,0.9847456,0.00002321397,0.0001830651,0.00008644299,0.00007153367,0.000633346,0.001959669,0.00005025023,0.00006102247,0.01099309],"study_design_scores_gemma":[0.00006293666,0.0008284028,0.9835713,0.00002118809,0.0001399887,0.001144788,0.0001046938,0.01198086,0.001758208,0.0001647242,0.0001930335,0.00002996503],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9971381,0.0006127014,0.001811409,0.00002476818,0.000007779294,0.00001503255,0.00004886957,0.00002408329,0.0003172551],"genre_scores_gemma":[0.9986615,0.00006104217,0.001132668,0.00001701109,0.00001294231,0.000006794679,0.00007100531,0.000004246013,0.00003277447],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003834086,"threshold_uncertainty_score":0.02027684,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07489472617816244,"score_gpt":0.4178362213186319,"score_spread":0.3429414951404694,"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."}}