{"id":"W4289535324","doi":"10.1016/j.hlc.2022.06.225","title":"Automated Assessment of CT Coronary Artery Stenosis Using a Deep Learning Approach","year":2022,"lang":"en","type":"article","venue":"Heart Lung and Circulation","topic":"Cardiac Imaging and Diagnostics","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Ottawa","funders":"","keywords":"Medicine; Coronary angiography; Stenosis; Radiology; Artery; Cardiology; Internal medicine; 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":[],"consensus_categories":[],"category_scores_codex":[0.0002294263,0.00006468304,0.0001775268,0.00008659079,0.0001847669,0.00001156637,0.00001154554,0.00001443184,0.00002241275],"category_scores_gemma":[0.0000269233,0.00007089494,0.0000560875,0.0001390058,0.00002119952,0.00003856701,0.0000290325,0.000147531,3.18289e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00009318453,"about_ca_system_score_gemma":0.00005424712,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003649843,"about_ca_topic_score_gemma":8.896674e-8,"domain_scores_codex":[0.9992732,0.0001010978,0.0001518056,0.0001442346,0.0002248583,0.0001048046],"domain_scores_gemma":[0.9997022,0.00006176631,0.00005289071,0.0000990242,0.000039462,0.00004472395],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00001116829,0.00008604558,0.9260667,0.00009534317,0.00004292329,0.00001275162,0.000207392,0.06880124,0.003864333,0.00002667695,0.00007601215,0.0007094056],"study_design_scores_gemma":[0.0003259012,0.0000326912,0.5315772,0.00001662643,0.00009139384,0.0003516938,0.0002427089,0.4672472,0.000009383688,0.000003818454,0.00006300067,0.00003839574],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9953675,0.0004905774,0.003009189,0.00006063191,0.00008056148,0.000188076,0.000003182743,0.0001190523,0.0006812739],"genre_scores_gemma":[0.9978878,0.000005654604,0.001849831,0.00008859044,0.00003217583,0.00001484459,0.00009281524,0.0000127775,0.00001547681],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.398446,"threshold_uncertainty_score":0.2891012,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02091328263589006,"score_gpt":0.3029086676559864,"score_spread":0.2819953850200964,"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."}}