{"id":"W2007646009","doi":"10.4155/bio.11.155","title":"Advances in Metabolite Identification","year":2011,"lang":"en","type":"review","venue":"Bioanalysis","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":276,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology","funders":"Canadian Institutes of Health Research","keywords":"Metabolomics; Metabolite; Identification (biology); Computational biology; Metabolite profiling; Biochemical engineering; Computer science; Chemistry; Biology; Bioinformatics; Biochemistry; Engineering","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":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0003210642,0.0003071532,0.001160205,0.0004296067,0.00004113804,0.00002339841,0.0003285165,0.0002233287,0.00003888795],"category_scores_gemma":[0.00009637125,0.0002467308,0.000650308,0.0006896392,0.00005490972,0.00000452986,0.0001335288,0.0001071537,0.00004645066],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002107346,"about_ca_system_score_gemma":0.00005561598,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001775034,"about_ca_topic_score_gemma":0.00008487039,"domain_scores_codex":[0.9983543,0.0001272736,0.0006018295,0.0005881704,0.00009538088,0.0002330774],"domain_scores_gemma":[0.9989125,0.00001022242,0.0003831592,0.0005944223,0.00005282381,0.00004687437],"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":[0.00000219314,0.00003494156,0.00003148825,0.0007002037,0.0003765192,0.000001040981,0.000004728042,1.900185e-7,0.00003161288,0.0005595098,0.00002988873,0.9982277],"study_design_scores_gemma":[0.00005660243,0.00001332122,0.00002641123,0.000110334,0.001281746,0.000001814425,0.000009111274,6.069613e-7,0.00005248759,0.00007525703,0.9981146,0.0002576488],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.000004221992,0.996769,0.0001749261,0.000003349262,0.000173619,0.0001842527,0.00005530366,0.000006573108,0.002628754],"genre_scores_gemma":[0.0001042732,0.9976946,0.0002871464,0.000009625763,0.0001555847,0.000113376,0.000466323,0.00002878933,0.001140325],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.9980848,"threshold_uncertainty_score":0.9999985,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02805667307163814,"score_gpt":0.3280089473840301,"score_spread":0.299952274312392,"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."}}