{"id":"W3112963515","doi":"10.1172/jci139927","title":"Biomarkers of inflammation and repair in kidney disease progression","year":2020,"lang":"en","type":"article","venue":"Journal of Clinical Investigation","topic":"Acute Kidney Injury Research","field":"Medicine","cited_by":185,"is_retracted":false,"has_abstract":true,"ca_institutions":"Western University","funders":"National Center for Advancing Translational Sciences; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; National Institutes of Health; Akebia Therapeutics","keywords":"Kidney disease; Medicine; Acute kidney injury; Inflammation; Disease; Kidney; Intensive care medicine; Bioinformatics; Pathology; Internal medicine; Biology","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":"codex-gemma-dda1882f352a","candidate_categories":["metaresearch"],"consensus_categories":[],"category_scores_codex":[0.001882274,0.00006851395,0.000351941,0.0001337219,0.00001375143,0.000005987923,0.00005818874,0.00009748944,0.00002835381],"category_scores_gemma":[0.02414724,0.0000512698,0.0001299008,0.0002864709,0.0002530121,0.0002436394,0.00003579321,0.0003736905,0.000002538016],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002152746,"about_ca_system_score_gemma":0.0007856462,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001911406,"about_ca_topic_score_gemma":2.43127e-7,"domain_scores_codex":[0.9976625,0.0002599026,0.001390671,0.0001211553,0.0004763737,0.00008933309],"domain_scores_gemma":[0.9974117,0.0002589543,0.0007118551,0.00009828265,0.0003034278,0.001215742],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.003272262,0.00008423669,0.949099,0.0005127817,0.00007910541,0.00008211035,0.0002215895,0.000001673915,0.01449846,0.00006479771,0.02098423,0.01109975],"study_design_scores_gemma":[0.005330711,0.002128934,0.962522,0.001762276,0.000167443,0.00001970926,0.0000808721,0.01477323,0.007631646,0.00128154,0.004213475,0.00008817853],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9406706,0.0001126621,0.00004884275,0.05874592,0.00007578486,0.0002371031,0.00001032031,0.00001086634,0.00008786154],"genre_scores_gemma":[0.9914372,0.0001782917,0.006253287,0.001677908,0.0004092538,0.000002941618,0.00001814648,0.000009513964,0.0000134461],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05706802,"threshold_uncertainty_score":0.9840728,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1104574868718401,"score_gpt":0.4407257322499085,"score_spread":0.3302682453780684,"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."}}