{"id":"W2626777690","doi":"10.2337/db16-1170","title":"Kv2.1 Clustering Contributes to Insulin Exocytosis and Rescues Human β-Cell Dysfunction","year":2017,"lang":"en","type":"article","venue":"Diabetes","topic":"Pancreatic function and diabetes","field":"Medicine","cited_by":55,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institutes of Health; National Institute of Diabetes and Digestive and Kidney Diseases; Alberta Innovates; Killam Trusts; Alberta Diabetes Foundation; University of Alberta; Canada Foundation for Innovation; Colorado State University","keywords":"Exocytosis; Human insulin; Insulin; Cluster analysis; Cell; Cell biology; Medicine; Biology; Chemistry; Internal medicine; Computer science; Genetics; Artificial intelligence","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":[0.000165847,0.0005280229,0.0005604994,0.0002454509,0.0002653924,0.0004545778,0.0003461213,0.0004257843,0.001722026],"category_scores_gemma":[0.0001334988,0.0002342841,0.0004909416,0.0002634663,0.0001909509,0.0001609589,0.000448428,0.0007805709,0.0008756212],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003651282,"about_ca_system_score_gemma":0.0002448808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001164437,"about_ca_topic_score_gemma":0.0008980514,"domain_scores_codex":[0.9997908,0.00002475137,0.00003572896,0.00005870228,0.00004537944,0.0000445108],"domain_scores_gemma":[0.9998626,0.000008525317,0.00004095619,0.00002508212,0.0000139635,0.00004884315],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0001886299,0.00004779187,0.0001488372,0.00004467668,0.00001527878,0.000101482,0.00001287898,0.00007961153,0.9982231,0.0000463106,0.0001640119,0.0009274397],"study_design_scores_gemma":[0.00008528576,0.0003735068,0.007862226,0.00002171543,0.0000677395,0.001030703,0.00004946857,0.001514899,0.9816428,0.0000713195,0.007266533,0.0000137725],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9914499,0.001696434,0.003441597,0.0002681163,0.00009918147,0.00007193859,0.001271878,0.0003018888,0.001399092],"genre_scores_gemma":[0.9904489,0.001183793,0.00254159,0.0001312597,0.00001846176,0.00006768705,0.001733981,0.000177239,0.003697168],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001722026,"threshold_uncertainty_score":0.005760789,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02175137214251915,"score_gpt":0.271845857647225,"score_spread":0.2500944855047058,"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."}}