{"id":"W4322627241","doi":"10.1016/j.trac.2023.117009","title":"Quantitative challenges and their bioinformatic solutions in mass spectrometry-based 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":15,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; University of British Columbia; Canada Foundation for Innovation","keywords":"Metabolomics; Computer science; Data science; Quantitative analysis (chemistry); Biochemical engineering; Computational biology; Chemistry; Biology; Chromatography; 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":[0.03557391,0.002324297,0.002554976,0.002884167,0.001735082,0.01102333,0.005006965,0.003982997,0.003200278],"category_scores_gemma":[0.06070205,0.001497014,0.001157161,0.003565981,0.007669601,0.0120316,0.005596829,0.008934724,0.001641946],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.003294603,"about_ca_system_score_gemma":0.003536276,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001633378,"about_ca_topic_score_gemma":0.002182274,"domain_scores_codex":[0.9838998,0.007507025,0.0009478476,0.001894278,0.00536265,0.0003883924],"domain_scores_gemma":[0.9463834,0.03860879,0.002985269,0.004415031,0.006880772,0.0007267253],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"theoretical_or_conceptual","study_design_gemma":"theoretical_or_conceptual","study_design_scores_codex":[0.0003501064,0.0004515623,0.004048262,0.00309276,0.0003718002,0.0003161633,0.0007011874,0.01607607,0.03209607,0.6141475,0.01234379,0.3160047],"study_design_scores_gemma":[0.00003012771,0.000103256,0.00118792,0.0002960524,0.00007242587,0.0003511643,0.000443712,0.09034185,0.01133092,0.8750004,0.02070923,0.0001328169],"study_design_candidate":"theoretical_or_conceptual","study_design_consensus":"theoretical_or_conceptual","genre_codex":"methods","genre_gemma":"methods","genre_scores_codex":[0.007600601,0.02066328,0.9370989,0.02775733,0.00106199,0.0001551628,0.0004527004,0.001057283,0.004152928],"genre_scores_gemma":[0.1078104,0.01797495,0.8589755,0.006950055,0.003194418,0.0006790623,0.0005919502,0.0004453363,0.003378344],"genre_candidate":"methods","genre_consensus":"methods","teacher_disagreement_score":0.03557391,"threshold_uncertainty_score":0.1881351,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04930373404580064,"score_gpt":0.2979800184092311,"score_spread":0.2486762843634305,"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."}}