{"id":"W4391151349","doi":"10.1111/dom.15463","title":"Postprandial glucose‐management strategies in type 1 diabetes: Current approaches and prospects with precision medicine and artificial intelligence","year":2024,"lang":"en","type":"article","venue":"Diabetes Obesity and Metabolism","topic":"Diabetes Management and Research","field":"Medicine","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"McGill University","keywords":"Postprandial; Type 2 diabetes; Medicine; Insulin; Diabetes mellitus; Meal; Internal medicine; Endocrinology; Intensive care medicine; Bioinformatics; Biology","routes":{"ca_aff":true,"ca_fund":true,"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":[0.005995102,0.001221046,0.002186541,0.001602283,0.0004240367,0.00311323,0.001366616,0.002355237,0.002605068],"category_scores_gemma":[0.007903798,0.0003552601,0.002218804,0.001480097,0.001567506,0.003290709,0.001679482,0.003710971,0.0007173246],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001527505,"about_ca_system_score_gemma":0.003615247,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002666068,"about_ca_topic_score_gemma":0.002558931,"domain_scores_codex":[0.9979427,0.0009246763,0.0002468311,0.000317538,0.0004562972,0.0001118202],"domain_scores_gemma":[0.9927291,0.005570301,0.0005430374,0.0002003366,0.0008101239,0.0001469303],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003450305,0.000139431,0.001577477,0.02447774,0.0005482713,0.0002211413,0.0004584879,0.002198775,0.0008650686,0.02657673,0.01314141,0.9294505],"study_design_scores_gemma":[0.000232903,0.001394843,0.005919697,0.05353286,0.002280404,0.001513822,0.001522194,0.007171673,0.003047942,0.1225398,0.8004884,0.0003553119],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000987745,0.97895,0.00746568,0.009517708,0.0006118063,0.00003528541,0.00007267143,0.00006627343,0.002292887],"genre_scores_gemma":[0.01827546,0.9604735,0.01379868,0.005222568,0.001249892,0.0001340454,0.0001286999,0.00002034411,0.0006967413],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.005995102,"threshold_uncertainty_score":0.0317055,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04824717584236721,"score_gpt":0.2997258717400016,"score_spread":0.2514786958976344,"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."}}