{"id":"W2973409925","doi":"10.3390/metabo9100200","title":"The metaRbolomics Toolbox in Bioconductor and beyond","year":2019,"lang":"en","type":"review","venue":"Metabolites","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":95,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"National Cancer Institute; Medical Research Council; Alberta Water Research Institute; National Institutes of Health; Agence Nationale de la Recherche; Ministerium für Kultur und Wissenschaft des Landes Nordrhein-Westfalen; Horizon 2020 Framework Programme; International Max Planck Research School for Advanced Methods in Process and Systems Engineering; Fonds National de la Recherche Luxembourg; World Health Organization; European Commission; Bundesministerium für Bildung und Forschung","keywords":"Workflow; Toolbox; Computer science; Bioconductor; Metabolomics; Scripting language; Data science; Identification (biology); Software; Data mining; Bioinformatics; Database; Chemistry; Biology","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.004987258,0.004901934,0.004455978,0.006085841,0.0007716281,0.004320598,0.00606782,0.002200959,0.07691505],"category_scores_gemma":[0.01145527,0.002079252,0.003226722,0.007383278,0.001355598,0.003703817,0.00332311,0.005665254,0.1260654],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009453163,"about_ca_system_score_gemma":0.004628899,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002250907,"about_ca_topic_score_gemma":0.001688984,"domain_scores_codex":[0.9973534,0.0008207909,0.0004369014,0.0005337732,0.0006500423,0.0002050699],"domain_scores_gemma":[0.9942059,0.002745115,0.0006619286,0.0008906908,0.00111784,0.0003785501],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0006151559,0.00008159005,0.0007251073,0.02341555,0.0009857143,0.000606392,0.0004955589,0.003254109,0.00642293,0.03262653,0.6176953,0.3130761],"study_design_scores_gemma":[0.0001251108,0.00004358078,0.0006682749,0.002337918,0.0002209754,0.000398569,0.00004991041,0.002050966,0.00422359,0.02168608,0.9680788,0.0001163277],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"software","genre_gemma":"software","genre_scores_codex":[0.001507225,0.08739799,0.3618059,0.003275137,0.00265748,0.0007003667,0.09046025,0.4051339,0.04706176],"genre_scores_gemma":[0.01586729,0.1026487,0.5220158,0.007418274,0.001890632,0.007599214,0.1596393,0.1532042,0.02971661],"genre_candidate":"software","genre_consensus":"software","teacher_disagreement_score":0.07691505,"threshold_uncertainty_score":0.2573065,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03235704521039688,"score_gpt":0.3096084466187805,"score_spread":0.2772514014083836,"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."}}