{"id":"W4282019082","doi":"10.1109/tmi.2022.3176814","title":"Volumetric Fetal Flow Imaging With Magnetic Resonance Imaging","year":2022,"lang":"en","type":"article","venue":"IEEE Transactions on Medical Imaging","topic":"Fetal and Pediatric Neurological Disorders","field":"Medicine","cited_by":19,"is_retracted":false,"has_abstract":true,"ca_institutions":"Mount Sinai Hospital; SickKids Foundation; University of Toronto","funders":"Peterborough K. M. Hunter Charitable Foundation; Canadian Institutes of Health Research; Hospital for Sick Children; University of Toronto","keywords":"Magnetic resonance imaging; Blood flow; Ductus venosus; Cardiac cycle; Cardiac imaging; Inferior vena cava; Medicine; Multislice; Biomedical engineering; Computer science; Nuclear medicine; Radiology; Fetus; Cardiology; Pregnancy","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","insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.0003946387,0.0003161735,0.0003802334,0.0004940902,0.0006466217,0.00004269419,0.0002842127,0.00003519305,0.006219248],"category_scores_gemma":[0.00006684416,0.000264065,0.000209368,0.001487888,0.0003480582,0.0001630754,0.00001234021,0.001613384,0.00008807595],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001205469,"about_ca_system_score_gemma":0.0002194866,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000117083,"about_ca_topic_score_gemma":0.000007182788,"domain_scores_codex":[0.996449,0.0001632753,0.0004097223,0.0006894915,0.001609117,0.0006793974],"domain_scores_gemma":[0.998719,0.0002650222,0.0000673164,0.0003697355,0.00007041826,0.0005084955],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0005597824,0.000706323,0.01095373,0.00004468335,0.00001537968,0.002362097,0.000113807,0.0009203069,0.0002166333,0.000005691621,0.002876776,0.9812248],"study_design_scores_gemma":[0.0121546,0.001311998,0.02182466,0.000174572,0.0006609877,0.007458351,0.001192997,0.8657355,0.0003371391,0.0002289014,0.0876416,0.001278633],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1092568,0.03036576,0.7603669,0.07511942,0.004567755,0.002172394,0.0002178774,0.001886707,0.01604633],"genre_scores_gemma":[0.9864841,0.0002080038,0.001128572,0.01070713,0.0001625004,0.0001486037,0.00001183718,0.00006534823,0.001083934],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9799461,"threshold_uncertainty_score":0.9999812,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007618771136247589,"score_gpt":0.2295964305456015,"score_spread":0.2219776594093539,"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."}}