{"id":"W3033038840","doi":"10.1007/s11306-020-01692-0","title":"SWATH-MS for metabolomics and lipidomics: critical aspects of qualitative and quantitative analysis","year":2020,"lang":"en","type":"review","venue":"Metabolomics","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":57,"is_retracted":false,"has_abstract":false,"ca_institutions":"Canadian Rheumatology Association","funders":"","keywords":"Lipidomics; Metabolomics; Computer science; Analyte; Data acquisition; Orbitrap; Data mining; Mass spectrometry; Computational biology; Bioinformatics; 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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004181976,0.002521351,0.003518864,0.003668244,0.0004237999,0.002747535,0.003161071,0.002876095,0.004343751],"category_scores_gemma":[0.002588142,0.0009778212,0.0009355753,0.004580158,0.001690259,0.004646219,0.00217152,0.005348345,0.00667948],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001428467,"about_ca_system_score_gemma":0.002580388,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001887872,"about_ca_topic_score_gemma":0.002771569,"domain_scores_codex":[0.9988071,0.0002180311,0.00009051264,0.000204556,0.0005955654,0.00008426372],"domain_scores_gemma":[0.9977075,0.001127314,0.0001769151,0.0001189326,0.0007405798,0.0001287974],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001308285,0.00009979415,0.0001115945,0.01169042,0.0001306278,0.0001340113,0.00003846582,0.0004145665,0.006944659,0.009734688,0.04102216,0.9295481],"study_design_scores_gemma":[0.00002290093,0.00008562757,0.0004367672,0.001358755,0.00009563557,0.0005793197,0.00004005685,0.0003917578,0.004531411,0.005630343,0.9867628,0.00006457451],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00008792539,0.9945483,0.0028279,0.0006812385,0.0005597804,0.0000170423,0.00007558306,0.00006025299,0.001141975],"genre_scores_gemma":[0.0005588765,0.9917086,0.004374185,0.000861785,0.0006365646,0.0000354846,0.0001815292,0.00002814845,0.001614781],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.004343751,"threshold_uncertainty_score":0.02211672,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07734240111978073,"score_gpt":0.4079500633390589,"score_spread":0.3306076622192781,"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."}}