{"id":"W2893496195","doi":"10.3390/metabo8040059","title":"A Framework for Development of Useful Metabolomic Biomarkers and Their Effective Knowledge Translation","year":2018,"lang":"en","type":"article","venue":"Metabolites","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":36,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of Waterloo","funders":"","keywords":"Metabolomics; Biomarker; Biomarker discovery; Medicine; Computer science; Data science; Bioinformatics; Proteomics; Biology","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":[0.00041634,0.000189052,0.0003277147,0.0001017393,0.0001288753,0.00001262017,0.000103179,0.000113603,0.000007928539],"category_scores_gemma":[0.0002081778,0.0001459851,0.0001013631,0.0001552581,0.000181806,0.000004571826,0.00006400982,0.00003934261,0.00000186132],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000004865618,"about_ca_system_score_gemma":0.00004318813,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001795285,"about_ca_topic_score_gemma":0.00001789753,"domain_scores_codex":[0.9990938,0.0000610196,0.0002502233,0.0003300884,0.00004798032,0.0002169261],"domain_scores_gemma":[0.9993711,0.0001281108,0.0001045199,0.0001903629,0.0001560503,0.00004985061],"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":[0.0002852415,0.00006770428,0.001131412,0.00004923866,0.0007182182,2.380989e-8,0.001051622,1.164598e-7,0.8969449,0.005645317,0.00007316581,0.09403308],"study_design_scores_gemma":[0.0004953322,0.0001858584,0.01121854,0.00001119036,0.00006842367,9.384568e-7,0.0001671736,0.0000363662,0.863524,0.002847781,0.1212812,0.0001632308],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8639622,0.03447979,0.1004196,0.00002983497,0.0002126789,0.0004916642,0.00004870179,0.000009896602,0.0003456741],"genre_scores_gemma":[0.877736,0.0003795737,0.1214477,0.00002775565,0.0002170451,0.000111978,0.00002624942,0.00001928582,0.0000343632],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.121208,"threshold_uncertainty_score":0.5953099,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03242787283194873,"score_gpt":0.3042749491803406,"score_spread":0.2718470763483919,"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."}}