{"id":"W4317490064","doi":"10.1016/j.thromres.2023.01.014","title":"Procoagulant phenotype induced by oxidized high-density lipoprotein associates with acute kidney injury and death","year":2023,"lang":"en","type":"article","venue":"Thrombosis Research","topic":"Neutrophil, Myeloperoxidase and Oxidative Mechanisms","field":"Immunology and Microbiology","cited_by":8,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia; Vancouver Coastal Health","funders":"Fondo Nacional de Desarrollo Científico y Tecnológico; Agencia Nacional de Investigación y Desarrollo; Instituto Milenio en Inmunología e Inmunoterapia; Ministerio de Ciencia, Tecnología, Conocimiento e Innovación","keywords":"Creatinine; Acute kidney injury; Internal medicine; Tissue factor; Kidney; Medicine; Cystatin C; Endocrinology; Endothelial activation; Lipoprotein; Coagulation; Inflammation; Cholesterol","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":["insufficient_payload"],"consensus_categories":[],"category_scores_codex":[0.001316949,0.0002925935,0.000553346,0.0003201405,0.0007265782,0.00007605748,0.0003657789,0.0003517193,0.0003192495],"category_scores_gemma":[0.0002146843,0.0002198885,0.00004842964,0.0008920112,0.0002698234,0.000163508,0.0004846704,0.0009117122,0.001315261],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0001043205,"about_ca_system_score_gemma":0.0002133846,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002082043,"about_ca_topic_score_gemma":0.00005340129,"domain_scores_codex":[0.9969876,0.0008171297,0.0002517629,0.0006845091,0.000251138,0.001007854],"domain_scores_gemma":[0.9988267,0.0001981971,0.00008467041,0.0004316806,0.0003244137,0.0001343192],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0004463076,0.0001267846,0.0003555766,0.00002784088,0.0005870314,0.0000187969,0.0003224622,2.093865e-8,0.9780355,0.001625144,0.01730352,0.001151028],"study_design_scores_gemma":[0.001608732,0.001176799,0.02360672,0.00007912236,0.0000598388,0.000006682564,0.0001493856,0.000001467617,0.9689811,0.001923491,0.00210796,0.0002986855],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9959471,0.0000924406,0.00001665922,0.002150305,0.000110634,0.0009450137,0.0002638232,0.0002443056,0.0002297222],"genre_scores_gemma":[0.9966002,0.000481555,0.0001279382,0.0002470948,0.0000414026,0.0002149542,0.0004537965,0.00005569115,0.001777345],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02325114,"threshold_uncertainty_score":0.9994623,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05696467714239761,"score_gpt":0.3388968038141106,"score_spread":0.281932126671713,"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."}}