{"id":"W4309648547","doi":"10.1016/s2589-7500(22)00197-2","title":"Treating type 2 diabetes: moving towards precision medicine","year":2022,"lang":"en","type":"letter","venue":"The Lancet Digital Health","topic":"Diabetes Treatment and Management","field":"Medicine","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"Jewish General Hospital","funders":"","keywords":"Type 2 diabetes; Precision medicine; Medicine; Diabetes mellitus; Computer science; Endocrinology; Pathology","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":[0.009424089,0.0009662556,0.001515846,0.001327466,0.002840814,0.006678822,0.002940479,0.03883515,0.02385885],"category_scores_gemma":[0.05214807,0.0006709612,0.001792976,0.001265339,0.005984683,0.01160142,0.003292301,0.04253157,0.01856177],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.005716269,"about_ca_system_score_gemma":0.005401341,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004273014,"about_ca_topic_score_gemma":0.008195627,"domain_scores_codex":[0.9899487,0.003128937,0.0009195363,0.0009222378,0.004425918,0.0006546794],"domain_scores_gemma":[0.9512012,0.03126365,0.001793129,0.001895296,0.008460755,0.005385915],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00003149862,0.00002091853,0.0001285189,0.0001684101,0.00001201188,0.0003322799,0.0000815911,0.0000466892,0.0001033389,0.00519331,0.9605326,0.03334884],"study_design_scores_gemma":[0.00007664682,0.00003996458,0.0003073162,0.0007498234,0.00001457006,0.0007992039,0.0001982493,0.0001770226,0.00009048669,0.02182305,0.9756896,0.00003405713],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"commentary","genre_gemma":"commentary","genre_scores_codex":[0.00006261804,0.007399639,0.00019771,0.9720847,0.01703312,0.000008435896,0.00004193565,0.00003268183,0.003139168],"genre_scores_gemma":[0.001859147,0.01219556,0.0009124334,0.9134901,0.06604707,0.00003125345,0.00004777495,0.00003776356,0.00537891],"genre_candidate":"commentary","genre_consensus":"commentary","teacher_disagreement_score":0.03883515,"threshold_uncertainty_score":0.0798158,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05056433100426944,"score_gpt":0.3240693205195262,"score_spread":0.2735049895152568,"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."}}