{"id":"W2008751190","doi":"10.4155/bio.09.138","title":"Computational Strategies for Metabolite Identification in Metabolomics","year":2009,"lang":"en","type":"review","venue":"Bioanalysis","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":119,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta; National Institute for Nanotechnology","funders":"Canadian Institutes of Health Research","keywords":"Metabolomics; Identification (biology); Metabolite; Computational biology; Metabolite profiling; Computer science; Data science; Biology; Bioinformatics; Biochemistry; Ecology","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":[0.001969821,0.001660951,0.002130972,0.001744093,0.0005756525,0.002226074,0.002733339,0.001292665,0.005974415],"category_scores_gemma":[0.004640901,0.0008101471,0.001421365,0.002311175,0.000905485,0.002403617,0.001759567,0.00153361,0.002496396],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0009374236,"about_ca_system_score_gemma":0.001550043,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002684947,"about_ca_topic_score_gemma":0.002503679,"domain_scores_codex":[0.9993984,0.0002663829,0.00004928919,0.000110561,0.0001511601,0.00002413778],"domain_scores_gemma":[0.9983522,0.001280033,0.00006650014,0.00009267767,0.0001747415,0.00003390753],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001457092,0.0001198272,0.001403242,0.003189514,0.0006469197,0.0003678877,0.0001400103,0.4600604,0.00323166,0.1655795,0.01035767,0.3547577],"study_design_scores_gemma":[0.00008345782,0.00007341662,0.0004329406,0.0003774582,0.0001543945,0.0002810819,0.00007542964,0.7420812,0.002605258,0.1938655,0.05989408,0.00007579278],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"review","genre_scores_codex":[0.002633616,0.01773194,0.9684547,0.001067491,0.0001932058,0.0001320869,0.0004190561,0.001076714,0.008291297],"genre_scores_gemma":[0.05176061,0.03187684,0.9095914,0.0005319402,0.000323668,0.0007751925,0.00114479,0.0003851762,0.003610385],"genre_candidate":"review","genre_consensus":null,"teacher_disagreement_score":0.005974415,"threshold_uncertainty_score":0.01998639,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03263139242311345,"score_gpt":0.3423896221457493,"score_spread":0.3097582297226358,"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."}}