{"id":"W2966057072","doi":"10.1016/j.neuroscience.2019.07.029","title":"Identification of Altered Metabolic Pathways during Disease Progression in EAE Mice via Metabolomics and Lipidomics","year":2019,"lang":"en","type":"article","venue":"Neuroscience","topic":"Sphingolipid Metabolism and Signaling","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"Ministry of Health, British Columbia; Korea Health Industry Development Institute; Korea Institute of Science and Technology; Ministry of Health and Welfare; Ministry of Science, ICT and Future Planning; National Science Foundation, United Arab Emirates; National Research Foundation","keywords":"Lipidomics; Metabolomics; Experimental autoimmune encephalomyelitis; Multiple sclerosis; Inflammation; Oxidative stress; Metabolite; Immune system; Metabolome; Metabolic pathway; Chemistry; Biology; Immunology; Biochemistry; Bioinformatics; Metabolism","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002681661,0.0001077542,0.0001559012,0.00008042503,0.00004670504,0.00002855524,0.0002117837,0.00004661927,0.000001213634],"category_scores_gemma":[0.0001539884,0.0001013368,0.00004015067,0.0001827498,0.00008863065,0.00002092,0.0001356413,0.00006624046,0.000001492547],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00000277203,"about_ca_system_score_gemma":0.00004277705,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000004687537,"about_ca_topic_score_gemma":0.000001405218,"domain_scores_codex":[0.9989086,0.00005666935,0.0002689292,0.0004282518,0.0001486564,0.0001889158],"domain_scores_gemma":[0.999432,0.000007935501,0.0001523423,0.0002848608,0.00003785193,0.00008502059],"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":[0.00007486829,0.00003861429,0.02922545,0.0000314204,0.000001054755,5.656089e-7,0.00005349686,0.0002295067,0.969524,0.00009952175,0.000001004884,0.0007205004],"study_design_scores_gemma":[0.0004567089,0.00002044345,0.2551002,0.00001188806,0.000009829302,0.000003782641,0.00001319324,0.002508801,0.7413782,0.00003684667,0.0003622788,0.00009775623],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9973552,0.001446045,0.0004035379,0.00002001368,0.0005194483,0.0002252355,0.00001263001,0.000006837173,0.00001105101],"genre_scores_gemma":[0.9989609,0.0006573722,0.0001432057,0.00008452097,0.00008805716,0.00001135815,0.000006005412,0.00001150042,0.00003708212],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.2281457,"threshold_uncertainty_score":0.4132394,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00850235749555745,"score_gpt":0.2416363365611487,"score_spread":0.2331339790655912,"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."}}