{"id":"W2764166773","doi":"10.1194/jlr.m079012","title":"Harmonizing lipidomics: NIST interlaboratory comparison exercise for lipidomics using SRM 1950–Metabolites in Frozen Human Plasma","year":2017,"lang":"en","type":"article","venue":"Journal of Lipid Research","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":411,"is_retracted":false,"has_abstract":true,"ca_institutions":"Concordia University; University of Victoria; McGill University; Hospital for Sick Children; Genome British Columbia; Jewish General Hospital","funders":"Advanced Low Carbon Technology Research and Development Program; Core Research for Evolutional Science and Technology; National Center for Advancing Translational Sciences; Office of Experimental Program to Stimulate Competitive Research; National Center for Research Resources; National Institute of Diabetes and Digestive and Kidney Diseases; National Heart, Lung, and Blood Institute; Natural Sciences and Engineering Research Council of Canada; Canadian Institutes of Health Research; National Institute of Standards and Technology; National Research Foundation Singapore; National Institute for Health Research Southampton Biomedical Research Centre; Directorate for Biological Sciences; National Institutes of Health; National Institute of General Medical Sciences; Warren Y. Soper Charitable Trust; National Cancer Institute; Genome Alberta; Japan Science and Technology Agency; Georgia Clinical and Translational Science Alliance; Vetenskapsrådet; Hjärt-Lungfonden; Austrian Science Fund; National University of Singapore; National Research Foundation; Leading Edge Endowment Fund; McGill University; Japan Agency for Medical Research and Development; Genome British Columbia; Fondation De Famille Alvin Segal; Steno Diabetes Center Copenhagen; Kansas IDeA Network of Biomedical Research Excellence; Jewish General Hospital; National Institute for Health and Care Research; Genome Canada; National Science Foundation","keywords":"Lipidomics; NIST; Workflow; Chemistry; Computer science; Biochemistry; Database","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":[0.07197011,0.001248184,0.0009874038,0.003888453,0.003501826,0.002756023,0.002157038,0.001627468,0.001457623],"category_scores_gemma":[0.04687558,0.0007728891,0.001808376,0.003027777,0.001659028,0.001334302,0.003695264,0.0012773,0.001026805],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001709409,"about_ca_system_score_gemma":0.00426276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005207335,"about_ca_topic_score_gemma":0.009529661,"domain_scores_codex":[0.9545149,0.01973442,0.003701431,0.006388233,0.01491326,0.0007477738],"domain_scores_gemma":[0.9759881,0.004835643,0.002381501,0.005789719,0.01067815,0.0003268191],"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":[0.004847805,0.002179486,0.1404244,0.001518358,0.002917138,0.001043909,0.008161319,0.01693921,0.5867312,0.005873243,0.008637336,0.2207265],"study_design_scores_gemma":[0.0004125264,0.004499593,0.2109196,0.0003946746,0.001314046,0.001838143,0.002884629,0.02491228,0.6924627,0.006456874,0.05335532,0.0005497232],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.5669175,0.001999875,0.4089229,0.001183753,0.0005256752,0.003909362,0.004711608,0.003110963,0.008718367],"genre_scores_gemma":[0.5063906,0.0005148595,0.4806221,0.0009323772,0.00009966891,0.001773548,0.006933328,0.0008956072,0.001837912],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.07197011,"threshold_uncertainty_score":0.3806189,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2014854625196821,"score_gpt":0.4454078019185686,"score_spread":0.2439223393988865,"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."}}