{"id":"W4283814285","doi":"10.2196/32366","title":"Machine Learning–Derived Prenatal Predictive Risk Model to Guide Intervention and Prevent the Progression of Gestational Diabetes Mellitus to Type 2 Diabetes: Prediction Model Development Study","year":2022,"lang":"en","type":"article","venue":"JMIR Diabetes","topic":"Gestational Diabetes Research and Management","field":"Medicine","cited_by":35,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Medical Research Council; Medical Research Council; National Institute for Health Research Southampton Biomedical Research Centre; National University Health System; National Research Foundation; Agency for Science, Technology and Research; British Heart Foundation; National Institute for Health and Care Research","keywords":"Gestational diabetes; Medicine; Machine learning; Population; Psychological intervention; Artificial intelligence; Predictive analytics; Logistic regression; Pregnancy; Computer science; Nursing; Environmental health; Gestation","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003202728,0.0007557825,0.0008742111,0.0007375888,0.0003720038,0.0006576242,0.0008117804,0.0007691734,0.002171274],"category_scores_gemma":[0.008600028,0.0002786973,0.0008273004,0.0003948153,0.0002634779,0.0004484851,0.000760104,0.001484172,0.000234312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001125705,"about_ca_system_score_gemma":0.00177999,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02416068,"about_ca_topic_score_gemma":0.01165935,"domain_scores_codex":[0.9994628,0.0003072344,0.00002228742,0.0000915182,0.0000473947,0.00006877576],"domain_scores_gemma":[0.9929807,0.005841118,0.0002273219,0.0001468622,0.0006618125,0.000142226],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0001825143,0.0002264595,0.01796384,0.00003749802,0.0001120906,0.00009434232,0.00005087212,0.9499227,0.0001576311,0.001852802,0.001086132,0.028313],"study_design_scores_gemma":[0.000005424128,0.00002306469,0.0003817068,0.000003791414,0.000006250431,0.000004170894,0.000004579075,0.9991807,0.00003890993,0.0003048356,0.00004489568,0.000001577992],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6557521,0.001117937,0.3345867,0.001856726,0.0001088817,0.0003540276,0.001061318,0.0006025768,0.004559739],"genre_scores_gemma":[0.9617334,0.0002404958,0.0355206,0.0001506437,0.0000267028,0.0001798568,0.000696029,0.00002107307,0.001431296],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02416068,"threshold_uncertainty_score":0.04804009,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01652511738049287,"score_gpt":0.3100800602825463,"score_spread":0.2935549429020534,"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."}}