{"id":"W4412406214","doi":"10.1371/journal.pone.0315484","title":"Urinary prostaglandin metabolites as biomarkers for human labour: Insights into future predictors","year":2025,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Preterm Birth and Chorioamnionitis","field":"Medicine","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"Canadian Institutes of Health Research","keywords":"Eicosanoid; Preterm labour; Prostaglandin; Metabolite; Arachidonic acid; Urinary system; Urine; Lipidomics; Medicine; Internal medicine; Endocrinology; Isoprostane; Pregnancy; Physiology; Obstetrics; Chemistry; Biology; Bioinformatics; Gestation; Biochemistry; Lipid peroxidation; Oxidative stress; Genetics","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":[0.004246948,0.0007693091,0.001141851,0.001048182,0.000263078,0.001574962,0.000607657,0.00069493,0.001489302],"category_scores_gemma":[0.007412635,0.0002971332,0.0004445594,0.001643855,0.0006371536,0.00101613,0.0005656141,0.00102085,0.0003202454],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003280343,"about_ca_system_score_gemma":0.0007981988,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001438489,"about_ca_topic_score_gemma":0.001514252,"domain_scores_codex":[0.9988864,0.0005855951,0.0001031259,0.0001887697,0.0001478147,0.00008833957],"domain_scores_gemma":[0.9958638,0.001892998,0.0009171399,0.0004560425,0.0004898723,0.0003802868],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.000631697,0.00008504608,0.9452861,0.0002403065,0.0002605792,0.0002061414,0.0001356202,0.0004239863,0.002835201,0.0006978545,0.0007663497,0.04843104],"study_design_scores_gemma":[0.00002525333,0.0006375962,0.9811251,0.0002241598,0.0003671456,0.0008760447,0.0004533494,0.005261544,0.001868696,0.003369549,0.005747327,0.00004416469],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8364952,0.1313354,0.01846431,0.007392005,0.0003860521,0.00008730168,0.002423739,0.0001895338,0.003226594],"genre_scores_gemma":[0.9704476,0.01691859,0.009405833,0.0006346388,0.0004085995,0.00005591725,0.001036998,0.00002815528,0.001063697],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.004246948,"threshold_uncertainty_score":0.02246028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01539919473889054,"score_gpt":0.2568795000869749,"score_spread":0.2414803053480844,"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."}}