{"id":"W2914122511","doi":"10.1159/000494615","title":"Magnetic Resonance Imaging: A New Tool to Optimize the Prediction of Fetal Anemia?","year":2019,"lang":"en","type":"article","venue":"Fetal Diagnosis and Therapy","topic":"Blood groups and transfusion","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"SickKids Foundation; Hospital for Sick Children; University of Toronto","funders":"","keywords":"Medicine; Magnetic resonance imaging; Fetus; Anemia; Pregnancy; Obstetrics; Radiology; Internal medicine","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":[0.002982523,0.001055324,0.0008936737,0.001839651,0.0001312583,0.0008484373,0.0006067042,0.001112222,0.001226974],"category_scores_gemma":[0.008709713,0.0002552716,0.0002458463,0.0005381792,0.0007517859,0.0008965155,0.0002677673,0.000703195,0.0006714301],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002707524,"about_ca_system_score_gemma":0.0003325659,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000472408,"about_ca_topic_score_gemma":0.0006374172,"domain_scores_codex":[0.9991183,0.0003882441,0.0000747114,0.0001724853,0.0002178488,0.00002850496],"domain_scores_gemma":[0.995685,0.002562309,0.0009211341,0.0001719956,0.0005115661,0.0001480205],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.001324148,0.0002261829,0.4639691,0.001174788,0.0003656021,0.00131592,0.0001541235,0.001256897,0.04485609,0.0007865087,0.005950162,0.4786204],"study_design_scores_gemma":[0.0003543878,0.004576438,0.7848995,0.002834469,0.001778578,0.04910596,0.0006098167,0.04351632,0.06313527,0.01176696,0.03707729,0.0003450094],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.649365,0.2132297,0.102705,0.0226378,0.001862018,0.0001809807,0.001126716,0.001506024,0.007386856],"genre_scores_gemma":[0.8603439,0.04199105,0.08900601,0.002367686,0.003286952,0.00009789274,0.0004506662,0.000123952,0.002331942],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002982523,"threshold_uncertainty_score":0.0157733,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01177630166724405,"score_gpt":0.2320847735970585,"score_spread":0.2203084719298144,"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."}}