{"id":"W4404375817","doi":"10.3390/metabo14110622","title":"A Comprehensive LC–MS Metabolomics Assay for Quantitative Analysis of Serum and Plasma","year":2024,"lang":"en","type":"article","venue":"Metabolites","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":27,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"Genome Alberta; Alberta Innovates; Ministerio de Ciencia, Innovación y Universidades; Centro de Investigación Biomédica en Red Fragilidad y Envejecimiento Saludable","keywords":"Metabolomics; Quantitative analysis (chemistry); Chromatography; Computational biology; Chemistry; Biology","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":[0.004421576,0.00313487,0.001335296,0.004210321,0.0009251402,0.001114656,0.00153071,0.002362629,0.004494493],"category_scores_gemma":[0.004526233,0.001131051,0.001582145,0.001864958,0.0009832967,0.0009414621,0.001342524,0.001847402,0.005544774],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009374396,"about_ca_system_score_gemma":0.002775964,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0005834477,"about_ca_topic_score_gemma":0.002009236,"domain_scores_codex":[0.9911879,0.002207865,0.000613594,0.001925293,0.003783504,0.0002818847],"domain_scores_gemma":[0.9970791,0.0006872971,0.0005081251,0.0003924936,0.001114968,0.000218019],"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":[0.0004672762,0.0003161686,0.006752302,0.0007610806,0.0002484714,0.0001627835,0.0000723031,0.0006249377,0.9246774,0.001144856,0.004287634,0.06048479],"study_design_scores_gemma":[0.0002045081,0.002110729,0.02136462,0.0002663603,0.0004064956,0.00278456,0.00005065128,0.01266597,0.9166116,0.001257857,0.04209259,0.0001839983],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.07190975,0.01484643,0.8787454,0.001029908,0.0008813919,0.003493363,0.008873731,0.00962714,0.01059292],"genre_scores_gemma":[0.1408682,0.004966244,0.8244836,0.002312942,0.0004533745,0.007036629,0.01044242,0.0004101328,0.009026425],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004494493,"threshold_uncertainty_score":0.0233838,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02202899798436024,"score_gpt":0.3000294911922882,"score_spread":0.278000493207928,"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."}}