{"id":"W3022658502","doi":"10.3390/metabo10050186","title":"MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics","year":2020,"lang":"en","type":"article","venue":"Metabolites","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":588,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"National Cancer Institute","keywords":"Workflow; Pipeline (software); Computer science; Benchmark (surveying); Metabolomics; Metabolome; Pipeline transport; Data mining; Key (lock); Computational biology; Bioinformatics; Chemistry; Database; 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":[0.007893923,0.00312674,0.002198647,0.002922926,0.001071948,0.004043777,0.003629154,0.001272982,0.005714018],"category_scores_gemma":[0.009806353,0.001856321,0.00259124,0.002160155,0.0008521163,0.002378454,0.00389123,0.003226086,0.006674936],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001223148,"about_ca_system_score_gemma":0.006260759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005748285,"about_ca_topic_score_gemma":0.006696064,"domain_scores_codex":[0.9977187,0.0004858234,0.0002927107,0.0006450792,0.0006757912,0.0001818866],"domain_scores_gemma":[0.9967463,0.0008601405,0.0004687,0.0006414105,0.001008817,0.0002745726],"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":[0.004170008,0.0003950202,0.01819557,0.005034611,0.002263624,0.00136378,0.001580895,0.04126087,0.3083297,0.02544051,0.2693074,0.3226579],"study_design_scores_gemma":[0.0006538981,0.0005049547,0.01084221,0.0006267892,0.0006147897,0.001403626,0.0003122891,0.3365683,0.3061983,0.03253138,0.308751,0.0009924679],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.00831629,0.0007832854,0.6829589,0.0007237962,0.0002450953,0.000304042,0.01470022,0.2907003,0.0012681],"genre_scores_gemma":[0.02729964,0.0008270575,0.9168372,0.0004392666,0.0000779039,0.000668204,0.02565883,0.0269935,0.001198438],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.007893923,"threshold_uncertainty_score":0.04174751,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0301003328465878,"score_gpt":0.2846727995211495,"score_spread":0.2545724666745617,"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."}}