{"id":"W2794316384","doi":"10.1016/j.ekir.2018.02.001","title":"Association Between Newborn Metabolic Profiles and Pediatric Kidney Disease","year":2018,"lang":"en","type":"article","venue":"Kidney International Reports","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":18,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Institute for Clinical Evaluative Sciences; Children's Hospital of Eastern Ontario; Ottawa Hospital","funders":"Canadian Institutes of Health Research; Ontario Ministry of Health and Long-Term Care; Academic Medical Organization of Southwestern Ontario; Institute for Clinical Evaluative Sciences; Bill and Melinda Gates Foundation","keywords":"Medicine; Kidney disease; Dialysis; Internal medicine; Logistic regression; Population; Cohort; Newborn screening; Pediatrics; Environmental health","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0003106165,0.0001449364,0.0001587037,0.0001010805,0.0001037485,0.00005398844,0.0001041904,0.00008237098,0.0001218385],"category_scores_gemma":[0.003380206,0.0001359103,0.00007484118,0.00009526584,0.00004344261,0.00001028817,0.0001770374,0.00006511867,0.00001242813],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002488939,"about_ca_system_score_gemma":0.0001957044,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001841685,"about_ca_topic_score_gemma":0.000002515692,"domain_scores_codex":[0.9987764,0.00002963374,0.0002974183,0.0003987605,0.0002979855,0.0001997443],"domain_scores_gemma":[0.9988034,0.00001338562,0.0002961989,0.0002133754,0.0002872367,0.0003864428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"not_applicable","study_design_scores_codex":[0.00002042987,0.00003153752,0.8731701,0.000009252683,0.0003485368,0.00001105189,0.00001663392,1.326659e-7,0.01184763,0.0003535511,0.1134957,0.0006953886],"study_design_scores_gemma":[0.0001973157,0.00003913528,0.2932587,0.000004290658,0.0001444388,0.000009329302,0.000004729526,0.000006247696,0.01308291,0.0008017878,0.6923075,0.0001436824],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9789939,0.0009235076,0.0006072604,0.005789288,0.001792044,0.0002415325,0.0003204397,0.00003221675,0.01129985],"genre_scores_gemma":[0.9841648,0.001226602,0.001384262,0.001201624,0.0041977,0.00003219008,0.0006217467,0.00002105281,0.007149976],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5799115,"threshold_uncertainty_score":0.5542262,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007897834727533313,"score_gpt":0.2566003644722571,"score_spread":0.2487025297447238,"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."}}