{"id":"W2053385401","doi":"10.1093/nar/gkn810","title":"HMDB: a knowledgebase for the human metabolome","year":2008,"lang":"en","type":"article","venue":"Nucleic Acids Research","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":1894,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Institute for Nanotechnology; University of Calgary; University of Alberta","funders":"Canadian Institutes of Health Research; Genome Alberta; Ministry of Advanced Education, Government of Alberta; Genome Canada","keywords":"Metabolome; Metabolomics; Matching (statistics); Software; Biology; Computer science; Database; Information retrieval; Computational biology; Bioinformatics","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":[0.002683597,0.002126572,0.003206288,0.01016477,0.001233097,0.004527688,0.004085584,0.002691344,0.0506385],"category_scores_gemma":[0.009691982,0.001378894,0.001988252,0.01011372,0.0005479376,0.004226491,0.004477459,0.002195682,0.03898054],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001222005,"about_ca_system_score_gemma":0.005495135,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.008901934,"about_ca_topic_score_gemma":0.008223145,"domain_scores_codex":[0.9984668,0.0002967574,0.0003918908,0.0003713343,0.0003476735,0.0001255414],"domain_scores_gemma":[0.9966235,0.001182872,0.0004422504,0.0006179303,0.000709355,0.000424131],"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":[0.0009375684,0.0001637437,0.002440465,0.009094105,0.0004568412,0.0009662057,0.0003228712,0.002270053,0.00432338,0.007377981,0.8165295,0.1551173],"study_design_scores_gemma":[0.0002552818,0.00007940122,0.003200188,0.001268713,0.0003131368,0.0008644456,0.0001527113,0.002124343,0.002302476,0.01133449,0.9779866,0.000118142],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"dataset","genre_gemma":"software","genre_scores_codex":[0.002528408,0.01191866,0.02950239,0.001387338,0.0004289783,0.0005065844,0.9240187,0.01837078,0.01133816],"genre_scores_gemma":[0.005024094,0.00718855,0.03824088,0.0008600278,0.0001340672,0.0006560372,0.9436497,0.001504198,0.002742313],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.0506385,"threshold_uncertainty_score":0.1694027,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.08576156402712931,"score_gpt":0.3756688929976746,"score_spread":0.2899073289705453,"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."}}