{"id":"W3035554388","doi":"10.1017/s0029665120000282","title":"Combined LC-MS and <sup>1</sup>H-NMR metabolomic profiling uncovers dietary biomarkers in a cohort of healthy Northern Irish older adults:","year":2020,"lang":"en","type":"article","venue":"Proceedings of The Nutrition Society","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Economic and Social Research Council","keywords":"Cohort; Metabolomics; Metabolome; Metabolite; Ingestion; Food science; Medicine; Chemistry; Animal science; Internal medicine; Chromatography; Biology","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.000601436,0.0004399662,0.0003858445,0.0005444986,0.0003766158,0.000714498,0.0003175805,0.0003445366,0.001432492],"category_scores_gemma":[0.0004912885,0.0002268597,0.0003248974,0.0005140175,0.0002620524,0.0001702295,0.0005339916,0.0003213385,0.0006654324],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004257622,"about_ca_system_score_gemma":0.0004088296,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01233737,"about_ca_topic_score_gemma":0.02317317,"domain_scores_codex":[0.9997098,0.00004846771,0.00002160577,0.0001028674,0.00007016629,0.00004710554],"domain_scores_gemma":[0.9996516,0.00002512235,0.00007606905,0.00004875393,0.0001535412,0.00004502981],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.004010187,0.0004141767,0.729415,0.0002416005,0.0004518041,0.0008698386,0.0007415217,0.0002628168,0.2265729,0.0000864246,0.002693614,0.03424003],"study_design_scores_gemma":[0.00003685918,0.0006564379,0.9804046,0.0000282956,0.000179317,0.0008757453,0.0005308777,0.0005600079,0.01356195,0.00005891277,0.00307919,0.00002804339],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9949185,0.0004234333,0.000829377,0.0001152034,0.00001325238,0.0000737635,0.002554056,0.00004301422,0.00102939],"genre_scores_gemma":[0.989113,0.0003812933,0.003390386,0.0003171497,0.00003198303,0.0001517528,0.003252234,0.00003857062,0.003323537],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01233737,"threshold_uncertainty_score":0.02453113,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009064947329140146,"score_gpt":0.2268761481137757,"score_spread":0.2178112007846355,"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."}}