{"id":"W4416934951","doi":"10.2196/79195","title":"Personalized Type 1 Diabetes Management: Reinforcement Learning–Based Insulin Dosing and Glucose Forecasting","year":2025,"lang":"en","type":"article","venue":"JMIR Diabetes","topic":"Diabetes Management and Research","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Type 1 diabetes; Dosing; Insulin; Diabetes mellitus; Reinforcement; Reinforcement learning","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":[0.0009724305,0.0007874611,0.0006870397,0.0003338025,0.0002383189,0.0005538255,0.0009909865,0.000632967,0.001263405],"category_scores_gemma":[0.003351395,0.0003048759,0.0004280534,0.0003107153,0.00032595,0.0006530188,0.0005427335,0.001366896,0.0002519918],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009349603,"about_ca_system_score_gemma":0.0009564785,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01589486,"about_ca_topic_score_gemma":0.0113698,"domain_scores_codex":[0.9996374,0.0001111528,0.00002082099,0.0001225572,0.00005853575,0.00004951792],"domain_scores_gemma":[0.999073,0.0005330821,0.0001308122,0.00005210469,0.0001475472,0.00006340557],"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":[0.0002047569,0.0002052277,0.005989932,0.0000600214,0.0000595576,0.00008936343,0.00003538964,0.9146309,0.0008529813,0.00109356,0.002843408,0.0739348],"study_design_scores_gemma":[0.0000109669,0.000018187,0.0002844996,0.000004619434,0.000006714004,0.000007110004,0.000002496436,0.998462,0.0001627992,0.0008163197,0.0002212182,0.000003140351],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1981716,0.004007678,0.783325,0.003312778,0.000419603,0.0001689624,0.001022587,0.002289076,0.007282691],"genre_scores_gemma":[0.960505,0.00047348,0.03670011,0.0003572549,0.00009237446,0.00007864242,0.0005117528,0.00003571321,0.00124568],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01589486,"threshold_uncertainty_score":0.03160471,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02094539813399459,"score_gpt":0.2891505882188016,"score_spread":0.268205190084807,"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."}}