{"id":"W4396989682","doi":"10.1681/asn.20223311s1229a","title":"Metabolic Profiling of Kidney Grafts: A Novel Approach for Allograft Monitoring in Transplantation","year":2022,"lang":"en","type":"article","venue":"Journal of the American Society of Nephrology","topic":"Renal Transplantation Outcomes and Treatments","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto; Hospital for Sick Children; Toronto General Hospital; University Health Network","funders":"","keywords":"Kidney transplantation; Transplantation; Medicine; Profiling (computer programming); Kidney; Urology; Intensive care medicine; Internal medicine; Computer science","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":[0.0007986828,0.0007072396,0.0008974235,0.001935768,0.0003071753,0.00139106,0.0005125143,0.0008154899,0.0008422976],"category_scores_gemma":[0.0006038377,0.0002452937,0.0004624797,0.00138715,0.0003439663,0.000716302,0.000701866,0.0009074022,0.0005123636],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003522221,"about_ca_system_score_gemma":0.0003456832,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0004376743,"about_ca_topic_score_gemma":0.0006782994,"domain_scores_codex":[0.9995214,0.0001052326,0.00002652502,0.000157056,0.0001488833,0.0000408897],"domain_scores_gemma":[0.9996195,0.00005560934,0.0001157313,0.00004115675,0.0001014565,0.00006661275],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.0007964246,0.0002052712,0.07902388,0.0007549837,0.0002913938,0.0003186973,0.0001443935,0.001164622,0.8047288,0.0006298021,0.001704552,0.1102371],"study_design_scores_gemma":[0.00007324046,0.001684861,0.3504264,0.0004199496,0.001003216,0.006191073,0.0008034534,0.05991733,0.5356773,0.006627701,0.0369611,0.0002143927],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.669107,0.0715763,0.2394102,0.002064345,0.0007655054,0.0002921449,0.007150142,0.001716163,0.007918196],"genre_scores_gemma":[0.8695614,0.02096788,0.1026931,0.0008292598,0.0004809979,0.0002547898,0.00249703,0.0001668998,0.002548606],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001935768,"threshold_uncertainty_score":0.004223883,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03134903047266853,"score_gpt":0.3095857819344463,"score_spread":0.2782367514617778,"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."}}