{"id":"W2090184061","doi":"10.1371/journal.pone.0006212","title":"Biomarkers for Early and Late Stage Chronic Allograft Nephropathy by Proteogenomic Profiling of Peripheral Blood","year":2009,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Renal Transplantation Outcomes and Treatments","field":"Medicine","cited_by":80,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"National Institute of Allergy and Infectious Diseases; Thailand Science Research and Innovation; Cleveland Clinic Foundation; National Institutes of Health; Cleveland Clinic","keywords":"Peripheral blood; Medicine; Profiling (computer programming); Nephropathy; Peripheral; Pathology; Internal medicine; Computer science; Endocrinology","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":[0.0004476688,0.0003289469,0.0003452894,0.00130414,0.0002052089,0.0006115533,0.0001632589,0.0003161423,0.0006822177],"category_scores_gemma":[0.0006337168,0.0000923098,0.0002831203,0.0009477139,0.0001586875,0.0001961937,0.0003155319,0.0003500095,0.0002554084],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001525469,"about_ca_system_score_gemma":0.0001766291,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003011373,"about_ca_topic_score_gemma":0.0005026971,"domain_scores_codex":[0.9997633,0.00004369033,0.00002084924,0.000072549,0.00006581929,0.00003386174],"domain_scores_gemma":[0.9996116,0.00008160155,0.0001631784,0.00002130887,0.00006776855,0.00005457479],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001043859,0.0002012189,0.7292923,0.0001907582,0.000233536,0.000309414,0.0001502218,0.0005878793,0.2388967,0.0001427196,0.0007704881,0.02818092],"study_design_scores_gemma":[0.00002064165,0.0004157459,0.9691713,0.00003367179,0.0001346349,0.001181116,0.0001966484,0.004067953,0.02288141,0.000459933,0.001419786,0.00001714499],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934476,0.001418925,0.002737874,0.0001465227,0.00001599773,0.00003487687,0.001644427,0.00004507149,0.0005086327],"genre_scores_gemma":[0.9922516,0.0004705047,0.004886756,0.0001523368,0.00003173398,0.00005058152,0.00183266,0.000008200694,0.0003156236],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.00130414,"threshold_uncertainty_score":0.002367556,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02529745439159889,"score_gpt":0.2526114466651722,"score_spread":0.2273139922735733,"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."}}