{"id":"W4400026810","doi":"10.1002/ansa.202400007","title":"Challenges and recent advances in quantitative mass spectrometry‐based metabolomics","year":2024,"lang":"en","type":"article","venue":"Analytical Science Advances","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":34,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université du Québec à Montréal","funders":"","keywords":"Metabolomics; Metabolite profiling; Computational biology; Computer science; Biochemical engineering; Chemistry; Chromatography; Biology","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007099829,0.0001745249,0.0002524622,0.0002972428,0.00009244993,0.0000719556,0.000232469,0.00004905932,0.00001571526],"category_scores_gemma":[0.0004823701,0.0001356298,0.00005152253,0.0009089207,0.0007238695,0.00006542611,0.0000962533,0.0001208318,0.000006340231],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003190704,"about_ca_system_score_gemma":0.00009920734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001901878,"about_ca_topic_score_gemma":0.0001062184,"domain_scores_codex":[0.9983013,0.00003512936,0.000218266,0.0007506064,0.0002706258,0.0004241263],"domain_scores_gemma":[0.9994927,0.00008477564,0.00003862809,0.0001968538,0.00007366349,0.0001133555],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001531512,0.0001400105,0.002149307,0.0001611503,0.0000833645,0.00003655676,0.00014599,0.0003586955,0.3769256,0.3581476,0.00004612598,0.2616524],"study_design_scores_gemma":[0.0008181109,0.001473966,0.01335618,0.000122158,0.0001054329,0.00001760288,0.001912432,0.01306003,0.1440739,0.05066298,0.7733437,0.001053558],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"empirical","genre_scores_codex":[0.09861109,0.8730454,0.006501799,0.002674778,0.000395288,0.0001765094,0.00001271791,0.00002885019,0.01855351],"genre_scores_gemma":[0.6054063,0.3823097,0.01201867,0.0001117847,0.00006516516,0.00001252559,0.000003551042,0.000009172204,0.00006316457],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.7732975,"threshold_uncertainty_score":0.5530823,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02806757338401677,"score_gpt":0.3386024289024024,"score_spread":0.3105348555183857,"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."}}