{"id":"W4381377683","doi":"10.2337/db23-434-p","title":"434-P: Urinary Proteome Classifiers in Prediabetes Clusters","year":2023,"lang":"en","type":"article","venue":"Diabetes","topic":"Advanced Proteomics Techniques and Applications","field":"Chemistry","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Prediabetes; Medicine; Diabetes mellitus; Internal medicine; Type 2 diabetes; Urine; Body mass index; Kidney disease; Diabetic nephropathy; Urinary system; Cohort; Endocrinology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001504242,0.0005502236,0.0005483857,0.001690892,0.0003907662,0.001324056,0.0003582189,0.0006208541,0.002889032],"category_scores_gemma":[0.003917603,0.0001304959,0.0005235102,0.001357838,0.0001706706,0.000594261,0.0009362833,0.000575135,0.00115056],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003823129,"about_ca_system_score_gemma":0.0004566377,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002078942,"about_ca_topic_score_gemma":0.001758497,"domain_scores_codex":[0.9993931,0.0001288773,0.00004875964,0.0001730139,0.0001407503,0.0001155699],"domain_scores_gemma":[0.9986894,0.0004568719,0.0002838708,0.0000927669,0.0002972025,0.0001800193],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003288751,0.0003153935,0.8585417,0.0001968568,0.0004436535,0.0002843314,0.0001972036,0.006212182,0.009396402,0.0002579778,0.008588092,0.1122776],"study_design_scores_gemma":[0.0001465056,0.001008228,0.8732241,0.00007763059,0.0001952286,0.001007541,0.0003926748,0.1086695,0.009634914,0.001545491,0.004042908,0.00005537151],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9831877,0.0006605837,0.005643212,0.000290159,0.00005756263,0.00008938358,0.007743804,0.0005738143,0.001753696],"genre_scores_gemma":[0.9824997,0.000137478,0.008498999,0.00007411679,0.00004684479,0.00008248942,0.007840145,0.0000444433,0.000775827],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002889032,"threshold_uncertainty_score":0.009664774,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01517980616416537,"score_gpt":0.2621388892909224,"score_spread":0.2469590831267571,"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."}}