{"id":"W2799810884","doi":"10.1016/j.chroma.2018.05.017","title":"Quantification of 38 dietary polyphenols in plasma by differential isotope labelling and liquid chromatography electrospray ionization tandem mass spectrometry","year":2018,"lang":"en","type":"article","venue":"Journal of Chromatography A","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Wereld Kanker Onderzoek Fonds; Institut National Du Cancer; Institute of Cancer Research; World Health Organization","keywords":"Chemistry; Chromatography; Labelling; Liquid chromatography–mass spectrometry; Electrospray; Polyphenol; Electrospray ionization; Mass spectrometry; Tandem mass spectrometry; Antioxidant; Biochemistry","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":[0.0003206093,0.0005027034,0.0003766064,0.0005786419,0.000544528,0.0004133754,0.0002864753,0.0005832218,0.001899846],"category_scores_gemma":[0.0005488858,0.0003317663,0.0003334269,0.0004988979,0.0004945052,0.0003336212,0.0003174985,0.0006402209,0.0004965963],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007287567,"about_ca_system_score_gemma":0.0008921708,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003091763,"about_ca_topic_score_gemma":0.005847956,"domain_scores_codex":[0.9997038,0.00004683908,0.00001165612,0.0001039432,0.00008538695,0.00004834186],"domain_scores_gemma":[0.9998373,0.00003869751,0.00002301479,0.00002060547,0.0000454851,0.00003489253],"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":[0.002285152,0.00009086749,0.004185753,0.0001115297,0.00007700529,0.00009666939,0.00008305439,0.000139463,0.975693,0.0002490946,0.0002564687,0.01673197],"study_design_scores_gemma":[0.0001883547,0.0008008106,0.04101378,0.00002784898,0.000125384,0.0004817162,0.0000728427,0.002985898,0.9476357,0.0005079674,0.006121893,0.00003790843],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9628571,0.005765495,0.02481818,0.0002955784,0.0001490202,0.0002136432,0.002652953,0.0003074385,0.002940746],"genre_scores_gemma":[0.9331816,0.003882581,0.04887288,0.0004065442,0.0000746027,0.0006653059,0.001917193,0.0001032336,0.01089604],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003091763,"threshold_uncertainty_score":0.006355584,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00806054200166373,"score_gpt":0.2358317431412206,"score_spread":0.2277712011395569,"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."}}