{"id":"W2899254389","doi":"10.1016/j.aca.2018.10.060","title":"Development of chemical isotope labeling LC-MS for tissue metabolomics and its application for brain and liver metabolome profiling in Alzheimer's disease mouse model","year":2018,"lang":"en","type":"article","venue":"Analytica Chimica Acta","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":36,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Alberta","funders":"Alberta Innovates; Alberta Prion Research Institute; Natural Sciences and Engineering Research Council of Canada; Canada Research Chairs; Canada Foundation for Innovation; Genome Canada","keywords":"Metabolome; Metabolomics; Metabolite; Chemistry; Chromatography; Biomarker discovery; Liquid chromatography–mass spectrometry; Mass spectrometry; Biochemistry; Proteomics; Gene","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":[0.0003360585,0.0001888751,0.0003424248,0.00009035698,0.0000789436,0.00001421728,0.0001348044,0.0001023182,0.00000135607],"category_scores_gemma":[0.0002438719,0.0001778533,0.00005222598,0.00009295494,0.00009078238,0.00001037975,0.000165673,0.00005169551,3.286087e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000008617069,"about_ca_system_score_gemma":0.00008403959,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001540952,"about_ca_topic_score_gemma":0.00001480294,"domain_scores_codex":[0.9988087,0.00001480858,0.0003524937,0.0004811675,0.0000793145,0.000263494],"domain_scores_gemma":[0.9993722,0.00004356083,0.0001297012,0.0001998206,0.0001470346,0.0001076522],"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":[0.0002343547,0.00006897377,0.00009854995,0.00005578695,0.0002046525,4.20643e-8,0.0000916498,0.000001725813,0.9957457,0.002464884,0.00005144831,0.0009821925],"study_design_scores_gemma":[0.0007616229,0.00006133431,0.0001135006,0.000006733071,0.0002301883,5.599254e-7,0.00002537175,0.04468973,0.9492317,0.0003931365,0.004270263,0.000215899],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9941821,0.001327533,0.003026506,0.0003715217,0.0000174405,0.0009123174,0.0001274715,0.00000725765,0.00002782885],"genre_scores_gemma":[0.9331452,0.0005293821,0.0656803,0.0001521468,0.00008978074,0.0001913196,0.0001326514,0.00002624707,0.00005299094],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.06265379,"threshold_uncertainty_score":0.7252646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02265441402668687,"score_gpt":0.285300582729399,"score_spread":0.2626461687027121,"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."}}