{"id":"W3006398297","doi":"10.1159/000505091","title":"Understanding Fetal Hemodynamics Using Cardiovascular Magnetic Resonance Imaging","year":2020,"lang":"en","type":"review","venue":"Fetal Diagnosis and Therapy","topic":"Congenital Heart Disease Studies","field":"Medicine","cited_by":38,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; University of Toronto; Hospital for Sick Children","funders":"","keywords":"Medicine; Ductus venosus; Fetus; Fetal circulation; Circulatory system; Cardiology; Blood flow; Magnetic resonance imaging; Hemodynamics; Intracardiac injection; Internal medicine; Placental Circulation; Placenta; Radiology; Pregnancy; Biology","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":[0.0007825986,0.0004165036,0.0003602903,0.001634651,0.0001773607,0.001045823,0.0005629046,0.000971615,0.001017623],"category_scores_gemma":[0.00197958,0.0002554727,0.0002547374,0.0005924767,0.0005925546,0.001115439,0.0004298046,0.0008665613,0.0003193515],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003541533,"about_ca_system_score_gemma":0.0004597359,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003165967,"about_ca_topic_score_gemma":0.002185444,"domain_scores_codex":[0.9997677,0.0000629924,0.00002007589,0.00005467037,0.00007465267,0.00001994614],"domain_scores_gemma":[0.9995661,0.0002291606,0.00007623059,0.00003165628,0.00006910993,0.00002771076],"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":[0.0001302339,0.0001036294,0.03825685,0.00127633,0.00010485,0.002454355,0.0008826073,0.01191987,0.1499029,0.01248585,0.005538364,0.7769442],"study_design_scores_gemma":[0.00008074761,0.001371986,0.3813048,0.003471155,0.0005951027,0.03461172,0.001917023,0.179877,0.1107627,0.05664099,0.2287503,0.0006164674],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.1668549,0.1602342,0.6365222,0.005989925,0.0004835679,0.0002209626,0.001162719,0.001668667,0.02686284],"genre_scores_gemma":[0.647743,0.1533623,0.1912923,0.00200178,0.001778949,0.0002638704,0.0007099502,0.0001394284,0.002708402],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.003165967,"threshold_uncertainty_score":0.006295085,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1255421087549876,"score_gpt":0.3282543261425363,"score_spread":0.2027122173875487,"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."}}