{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005464937,0.0002703944,0.0004093479,0.0005721599,0.0002786166,0.0001564858,0.0001512826,0.00009973837,0.0002377319],"category_scores_gemma":[0.0001855699,0.000237162,0.0001097553,0.0008127119,0.0001966766,0.0001347926,0.0002764013,0.0003276347,0.00004308302],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00008628464,"about_ca_system_score_gemma":0.00004432425,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001361886,"about_ca_topic_score_gemma":4.513903e-7,"domain_scores_codex":[0.9980178,0.00007583978,0.0003276446,0.0004497703,0.0004072453,0.0007217356],"domain_scores_gemma":[0.9991381,0.0001994754,0.00009226028,0.0002883589,0.0001304085,0.0001514356],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0004303184,0.0004956615,0.6179382,0.008408118,0.001440715,0.0000507022,0.0003343266,0.0006875795,0.006945283,0.002925807,0.007188795,0.3531545],"study_design_scores_gemma":[0.02108541,0.002401421,0.1781163,0.007222692,0.001311056,3.841917e-7,0.000926514,0.4709367,0.02419658,0.001466097,0.2908726,0.001464318],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9622931,0.002994444,0.00007040845,0.001164229,0.0001670194,0.001291168,0.000001163629,0.0002081784,0.03181027],"genre_scores_gemma":[0.977935,0.0001101879,0.0006943571,0.001081607,0.00007672363,0.0001815924,0.00008942343,0.00003664799,0.01979449],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4702491,"threshold_uncertainty_score":0.9671186,"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."}}