{"id":"W2811431920","doi":"10.1007/s00422-018-0765-y","title":"Optimizing SGLT inhibitor treatment for diabetes with chronic kidney diseases","year":2018,"lang":"en","type":"article","venue":"Biological Cybernetics","topic":"Diabetes Treatment and Management","field":"Medicine","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Waterloo","funders":"National Institute of Diabetes and Digestive and Kidney Diseases; National Institutes of Health","keywords":"Nephron; Tubuloglomerular feedback; Renal glucose reabsorption; Kidney; Endocrinology; Renal function; Internal medicine; Kidney disease; Diabetes mellitus; Natriuresis; Reabsorption; Medicine; Excretion; Population; Type 2 diabetes; Renal sodium reabsorption; Tubular fluid; Glomerular hyperfiltration; Diabetic nephropathy","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0000385886,0.0002388947,0.0003293082,0.00004419328,0.00009120551,0.00002940774,0.00007002142,0.00008560692,0.0001472319],"category_scores_gemma":[0.00006545348,0.000129224,0.0001206441,0.00009125297,0.0002524291,0.00002670565,0.00004844046,0.00003365408,0.00006139868],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002028242,"about_ca_system_score_gemma":0.00006875647,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000003588399,"about_ca_topic_score_gemma":0.000005493683,"domain_scores_codex":[0.9989159,0.00001837943,0.0001652813,0.0003616303,0.0001089751,0.0004298722],"domain_scores_gemma":[0.9992443,0.00007882887,0.00005704233,0.0002453833,0.00007754569,0.0002969421],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.003276367,0.007848777,0.6792324,0.000561495,0.003888866,0.0001096104,0.0004757351,0.00002675148,0.01975806,0.008127968,0.04673998,0.2299541],"study_design_scores_gemma":[0.01495922,0.08088502,0.05841155,0.0005017287,0.001882195,0.000003180889,0.00006165243,0.001166639,0.04296543,0.0005062936,0.7978564,0.0008007186],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9899817,0.001537365,0.0003115658,0.00147518,0.0002303149,0.00191663,0.00009768205,0.0002524915,0.004197117],"genre_scores_gemma":[0.9874809,0.0002280708,0.007492075,0.0009841007,0.001002925,0.000344099,0.0002971987,0.00002544034,0.002145156],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7511164,"threshold_uncertainty_score":0.5269602,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02841396132092979,"score_gpt":0.2669009618056504,"score_spread":0.2384870004847206,"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."}}