{"id":"W2077488126","doi":"10.1021/ac400099b","title":"MyCompoundID: Using an Evidence-Based Metabolome Library for Metabolite Identification","year":2013,"lang":"en","type":"article","venue":"Analytical Chemistry","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":234,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Alberta","funders":"","keywords":"Metabolome; Metabolomics; Metabolite; Chemistry; Identification (biology); Urine; Mass spectrometry; KEGG; Chromatography; Computational biology; Biochemistry; Biology; Transcriptome","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002336861,0.0002360153,0.0003156252,0.00004643065,0.0001373312,0.0001606754,0.0003310405,0.0001737456,0.000266085],"category_scores_gemma":[0.0003250129,0.0002167322,0.0002243828,0.0001987701,0.0001227021,0.00005388328,0.0001013927,0.00009762753,0.00001424215],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001373851,"about_ca_system_score_gemma":0.0001063576,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001498395,"about_ca_topic_score_gemma":3.81001e-7,"domain_scores_codex":[0.9984344,0.00004104507,0.0003846194,0.0005888241,0.0001740903,0.0003769677],"domain_scores_gemma":[0.9988563,0.00005828619,0.0001358258,0.0005837628,0.0001607647,0.000205041],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.00004242877,0.000112725,0.001109217,0.0000698533,0.0001344499,5.134275e-7,0.000003631925,0.00006583257,0.9962472,0.000306809,0.001595084,0.0003122331],"study_design_scores_gemma":[0.0004134268,0.00006114802,0.002196397,0.0000140333,0.0002303348,0.000004436489,0.000050005,0.01160964,0.9582925,0.000912403,0.02586033,0.0003553826],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9822741,0.004032686,0.01194304,0.0006042753,0.0001059201,0.000357548,0.00007201501,0.0000451457,0.0005653005],"genre_scores_gemma":[0.9887496,0.0002901088,0.007232735,0.0004839395,0.0006163074,0.0001065304,0.0004505711,0.00004605199,0.002024114],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.03795476,"threshold_uncertainty_score":0.8838082,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04315269006236453,"score_gpt":0.2990633695909473,"score_spread":0.2559106795285827,"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."}}