{"id":"W2904529089","doi":"10.1007/s00404-018-5003-2","title":"Does prenatal identification of fetal macrosomia change management and outcome?","year":2018,"lang":"en","type":"article","venue":"Archives of Gynecology and Obstetrics","topic":"Gestational Diabetes Research and Management","field":"Medicine","cited_by":31,"is_retracted":false,"has_abstract":false,"ca_institutions":"Health Sciences Centre; University of Toronto; Sunnybrook Health Science Centre","funders":"","keywords":"Medicine; Obstetrics; Fetal macrosomia; Identification (biology); Outcome (game theory); Fetus; Prenatal diagnosis; Pregnancy; Human genetics; Gynecology; Gestation; Genetics","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":[0.0001032623,0.00006267372,0.0001540415,0.0002659587,0.00004654449,0.000004820916,0.00005618812,0.00002831138,0.0000207286],"category_scores_gemma":[0.0004503887,0.00004290749,0.00002635006,0.000116781,0.000442426,0.00005120841,0.0001468129,0.00005255162,0.000002960351],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005847613,"about_ca_system_score_gemma":0.000006962407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005499621,"about_ca_topic_score_gemma":0.000007901733,"domain_scores_codex":[0.9993284,0.0000276722,0.0002285373,0.0001557601,0.0001203554,0.0001392615],"domain_scores_gemma":[0.9990656,0.0006098596,0.00009224919,0.0001245701,0.00004441669,0.00006324786],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0001580588,0.000236706,0.6524817,0.002123727,0.0002256926,0.00002056653,0.001200984,3.446527e-7,0.001810935,0.01138815,0.00006469264,0.3302884],"study_design_scores_gemma":[0.0009635279,0.0004085263,0.9913016,0.00002662168,0.00006073881,0.000001476418,0.000268222,0.0003235272,0.003088843,0.002127832,0.001383438,0.00004563891],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9958778,0.0005502977,0.0003091161,0.000382836,0.0001867201,0.0004656619,0.00003022244,0.000007827565,0.002189515],"genre_scores_gemma":[0.9951841,0.001018475,0.001985703,0.00007838973,0.00002076072,0.00002296924,0.00002618339,0.000004673505,0.001658706],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3388199,"threshold_uncertainty_score":0.1749717,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02071942230258371,"score_gpt":0.2940166773286298,"score_spread":0.2732972550260461,"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."}}