{"id":"W4414296654","doi":"10.2196/71539","title":"Interpretable Machine Learning for Predicting Adverse Pregnancy Outcomes in Gestational Diabetes: Retrospective Cohort Study","year":2025,"lang":"en","type":"article","venue":"JMIR Medical Informatics","topic":"Gestational Diabetes Research and Management","field":"Medicine","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Retrospective cohort study; Pregnancy; Adverse effect; Cohort study; Gestational age; MEDLINE; Cohort","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":[0.003728647,0.0003740394,0.0004279644,0.0009354852,0.0003750794,0.000786533,0.0005438694,0.0005551097,0.001129912],"category_scores_gemma":[0.01070116,0.0002817586,0.001008679,0.0009530858,0.000293616,0.0004642949,0.0005465338,0.001117161,0.0001844728],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000378863,"about_ca_system_score_gemma":0.0005384946,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00291811,"about_ca_topic_score_gemma":0.002478932,"domain_scores_codex":[0.9986485,0.0004802017,0.0001770473,0.0003337938,0.0002407455,0.0001198243],"domain_scores_gemma":[0.9951243,0.001532868,0.001358665,0.001326816,0.0003898339,0.0002676255],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002467999,0.00003514265,0.997086,0.00001359839,0.0001453115,0.0001019463,0.00005048592,0.0002251345,0.0001109173,0.00005338263,0.0001730467,0.001758254],"study_design_scores_gemma":[0.00003888779,0.0003126959,0.9912521,0.0000320841,0.0002926428,0.0008963742,0.000245399,0.005642059,0.0002145572,0.0003447221,0.0007073026,0.00002110551],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9970257,0.0003496151,0.001185367,0.00006496548,0.00001273869,0.00002812089,0.001135135,0.00001022641,0.0001881595],"genre_scores_gemma":[0.9978901,0.0001268536,0.0007070106,0.00001980152,0.000009583566,0.00003466949,0.001139729,0.000005860842,0.00006639029],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003728647,"threshold_uncertainty_score":0.01971918,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01048852076590323,"score_gpt":0.3263467797679157,"score_spread":0.3158582590020124,"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."}}