{"id":"W4387641474","doi":"10.1016/j.trac.2023.117364","title":"Controlling pre-analytical process in human serum/plasma metabolomics","year":2023,"lang":"en","type":"article","venue":"TrAC Trends in Analytical Chemistry","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":false,"ca_institutions":"The Metabolomics Innovation Centre; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Metabolome; Metabolomics; Human plasma; Process (computing); Computer science; Biochemical engineering; Computational biology; Bioinformatics; Biology; Chromatography; Chemistry; Engineering","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":[0.001427126,0.0009283553,0.0004988555,0.0005394488,0.0005998688,0.001299376,0.0005973149,0.0005780455,0.001368852],"category_scores_gemma":[0.00260111,0.0003432578,0.0003800329,0.0004238239,0.0005537287,0.0008020304,0.0008083566,0.00113545,0.0008821121],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004800979,"about_ca_system_score_gemma":0.001600107,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001659761,"about_ca_topic_score_gemma":0.002542367,"domain_scores_codex":[0.9988647,0.0002596885,0.00005847723,0.0002558344,0.0004450066,0.0001163522],"domain_scores_gemma":[0.999086,0.0004154846,0.0001122571,0.0001040209,0.0002274328,0.00005463252],"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":[0.0005733874,0.000149889,0.002970713,0.0001576928,0.00003258426,0.00007656577,0.0001050175,0.0006085329,0.9711905,0.0005365783,0.0005796159,0.02301895],"study_design_scores_gemma":[0.0000196231,0.0001930358,0.003171297,0.000008307772,0.00003126948,0.0001238937,0.0000384349,0.009530969,0.9837357,0.000343607,0.002779761,0.00002405773],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"methods","genre_scores_codex":[0.5203547,0.004385564,0.4639187,0.001165959,0.0006565198,0.0007295103,0.0008326396,0.003904028,0.004052291],"genre_scores_gemma":[0.8408943,0.002410166,0.1490834,0.001202058,0.000288616,0.0004280129,0.000683664,0.0005702943,0.004439464],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.001659761,"threshold_uncertainty_score":0.007547498,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02256375112038935,"score_gpt":0.3300173219738382,"score_spread":0.3074535708534489,"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."}}