{"id":"W2920332083","doi":"10.1194/jlr.d090571","title":"Quantitative metabolic profiling of urinary eicosanoids for clinical phenotyping","year":2019,"lang":"en","type":"article","venue":"Journal of Lipid Research","topic":"Eicosanoids and Hypertension Pharmacology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Vetenskapsrådet; Karolinska Institutet; Hjärt-Lungfonden; Stockholms Läns Landsting; AstraZeneca Canada; AllerGen; Canada Research Chairs; Stiftelsen för Strategisk Forskning; Vårdalstiftelsen","keywords":"Isoprostanes; Eicosanoid; Inflammation; Urinary system; Urine; Medicine; Asthma; Lipid signaling; Chemistry; Pharmacology; Oxidative stress; Internal medicine; Biochemistry; Arachidonic acid; Enzyme; Lipid peroxidation","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002572736,0.001078458,0.0008281079,0.001969779,0.0005759092,0.001536794,0.0004483645,0.0009010337,0.003594019],"category_scores_gemma":[0.003072304,0.0003264352,0.0005228081,0.002188043,0.000392804,0.0003706247,0.0006963043,0.0009137548,0.001610411],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002885151,"about_ca_system_score_gemma":0.0008325958,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0008682226,"about_ca_topic_score_gemma":0.002128226,"domain_scores_codex":[0.9971651,0.0007796847,0.0002561462,0.0006968803,0.0008789831,0.0002232282],"domain_scores_gemma":[0.9990139,0.0002022954,0.0002280841,0.0002339499,0.0002389474,0.00008289163],"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":[0.002789908,0.0006066085,0.1886535,0.0008457496,0.0007188464,0.0005678522,0.0002887705,0.0009151468,0.6717421,0.001407477,0.004124166,0.12734],"study_design_scores_gemma":[0.0001951565,0.001782337,0.536498,0.0003291727,0.0007826542,0.003432483,0.0003550208,0.009700894,0.4045401,0.00256778,0.03967547,0.0001410659],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.6524946,0.01643298,0.2692458,0.0007290082,0.001206859,0.001720392,0.03954369,0.002478563,0.01614815],"genre_scores_gemma":[0.8849927,0.00315595,0.08813142,0.0008790037,0.00024148,0.00258613,0.01237465,0.0004457546,0.00719296],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003594019,"threshold_uncertainty_score":0.01360607,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1981013430499207,"score_gpt":0.51074520327162,"score_spread":0.3126438602216993,"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."}}