{"id":"W2807316315","doi":"10.1111/petr.13226","title":"Non‐invasive staging of chronic kidney allograft damage using urine metabolomic profiling","year":2018,"lang":"en","type":"article","venue":"Pediatric Transplantation","topic":"Renal Transplantation Outcomes and Treatments","field":"Medicine","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"BC Children's Hospital; The Metabolomics Innovation Centre; University of Alberta; Manitoba Health; University of Manitoba; University of British Columbia; Children's Hospital of Winnipeg; Children's Hospital Research Institute of Manitoba; McMaster University","funders":"National Research Council Canada; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; BC Children's Hospital","keywords":"Medicine; Metabolite; Urine; Internal medicine; Metabolomics; Kidney transplantation; Proteinuria; Confounding; Urinary system; Kidney; Kidney disease; Metabolome; Creatinine; Urology; Gastroenterology; 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":[0.0009227418,0.0005320337,0.0006143765,0.0008429146,0.0001777177,0.0006796512,0.0001871403,0.0002381104,0.0004053877],"category_scores_gemma":[0.001448628,0.0001385747,0.0003433327,0.000675045,0.0002141947,0.0003500424,0.0003728157,0.0004131495,0.0001143727],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002508795,"about_ca_system_score_gemma":0.0003459598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001075821,"about_ca_topic_score_gemma":0.003457103,"domain_scores_codex":[0.9995756,0.000139138,0.00003623337,0.0001010934,0.0001105886,0.00003738704],"domain_scores_gemma":[0.999,0.0002137157,0.0005251132,0.00005496163,0.0001231888,0.00008312076],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005473933,0.0001167293,0.9075921,0.0001202486,0.0002658667,0.0001362146,0.00007021438,0.001142998,0.04644558,0.00008466612,0.0002151283,0.04326283],"study_design_scores_gemma":[0.00001344994,0.0007321257,0.9661297,0.00003398336,0.0001590195,0.0006611603,0.00009118614,0.0063224,0.02497533,0.0002077711,0.0006578122,0.00001590177],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9882089,0.002642414,0.007813357,0.00007501044,0.00001334322,0.00003129117,0.0006556628,0.00007557921,0.0004843904],"genre_scores_gemma":[0.9931414,0.0008396696,0.005313854,0.00004249563,0.00001217699,0.00001744388,0.000435646,0.000010623,0.0001868309],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001075821,"threshold_uncertainty_score":0.004879951,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01950750542000191,"score_gpt":0.2952390920615068,"score_spread":0.2757315866415049,"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."}}