{"id":"W2002114056","doi":"10.1002/elps.201400604","title":"Multiplexed separations for biomarker discovery in metabolomics: Elucidating adaptive responses to exercise training","year":2015,"lang":"en","type":"article","venue":"Electrophoresis","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":42,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Metabolomics; Hypoxanthine; Metabolome; Biomarker discovery; Chemistry; Internal medicine; Medicine; Proteomics; Biochemistry; Chromatography","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":[],"consensus_categories":[],"category_scores_codex":[0.0005332915,0.0002157017,0.0003388713,0.0002330927,0.0001068182,0.00005264722,0.000181674,0.00009733415,0.000003148882],"category_scores_gemma":[0.0009372135,0.000206448,0.0001189468,0.0003661135,0.00004002044,0.00001277467,0.0001031883,0.0000723905,0.000003932944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005187769,"about_ca_system_score_gemma":0.0001970381,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004661901,"about_ca_topic_score_gemma":0.000266697,"domain_scores_codex":[0.9985166,0.00008714153,0.0003020675,0.0004912937,0.0001275343,0.0004753543],"domain_scores_gemma":[0.9993089,0.00006985744,0.00008500003,0.0002802952,0.0001286862,0.0001272666],"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":[0.001981745,0.0000543336,0.0003824313,0.000004187264,0.0001001951,0.00000197946,0.0005557226,0.00007660816,0.9896919,0.0005269792,0.004063701,0.00256029],"study_design_scores_gemma":[0.002785007,0.00126762,0.006652296,0.00003273793,0.0001217687,0.000007434872,0.002999803,0.0006536195,0.9355329,0.001081745,0.04807369,0.000791404],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9810523,0.004349962,0.01277034,0.0003054521,0.0001591932,0.0007715983,0.0001159603,0.0000176603,0.0004575776],"genre_scores_gemma":[0.9736336,0.000411053,0.02385816,0.0001652442,0.0001357371,0.0004233037,0.00007916708,0.00003665659,0.001257082],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05415895,"threshold_uncertainty_score":0.8418707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06458161038500619,"score_gpt":0.3143578952583246,"score_spread":0.2497762848733184,"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."}}