{"id":"W7125586738","doi":"10.1109/ic3it66137.2025.11341169","title":"Machine Learning Meets Healthcare: Predicting Diabetes Onset With Ehr","year":2025,"lang":"","type":"article","venue":"","topic":"Machine Learning in Healthcare","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"Horizon College and Seminary","funders":"","keywords":"Diabetes mellitus; Feature (linguistics); MEDLINE; Training set; Deep learning","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":[0.001191352,0.0004919865,0.0005598481,0.001772029,0.000309415,0.001753796,0.0004045133,0.001123187,0.002133226],"category_scores_gemma":[0.01297991,0.0002411861,0.0005625007,0.001887194,0.00012499,0.001413174,0.0007741861,0.001136593,0.0009533173],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005425512,"about_ca_system_score_gemma":0.0007744085,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008680691,"about_ca_topic_score_gemma":0.01164948,"domain_scores_codex":[0.9990631,0.0003953391,0.00009023956,0.0001678849,0.0001650097,0.0001183879],"domain_scores_gemma":[0.9962095,0.00218271,0.0005004645,0.0002617603,0.0004497615,0.0003959034],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005521143,0.0005940933,0.8567988,0.00009229423,0.0001618211,0.0003164638,0.00006780816,0.005736032,0.0006744078,0.0007703724,0.01128048,0.1229553],"study_design_scores_gemma":[0.0001432306,0.0005909526,0.4425831,0.0001853219,0.0003783197,0.001336168,0.0006416859,0.5246685,0.00372596,0.0162987,0.009382291,0.00006582159],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9256877,0.004237585,0.03618433,0.01025997,0.0004740376,0.0001341326,0.01435894,0.001034261,0.00762913],"genre_scores_gemma":[0.974017,0.0007688104,0.01835296,0.0003734856,0.000219775,0.00002608276,0.005447766,0.0000310884,0.0007631],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.008680691,"threshold_uncertainty_score":0.01726037,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0117383861643784,"score_gpt":0.2765595318051533,"score_spread":0.2648211456407749,"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."}}