{"id":"W7028958363","doi":"","title":"Identifying the dietary signatures of arthritis through metabolomics","year":2024,"lang":"en","type":"article","venue":"UEA Digital Repository (University of East Anglia)","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Xunta de Galicia; Axencia Galega de Innovación","keywords":"Rheumatoid arthritis; Cluster analysis; Metabolomics; Deconvolution; Bottleneck; Metabolite; Arthritis","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00005831661,0.0001155003,0.0001929141,0.00004018743,0.0001311171,0.00004578002,0.0002436289,0.00008001623,0.000007097358],"category_scores_gemma":[0.00002489243,0.0001053351,0.0002421045,0.0001553364,0.0002648414,0.00003513734,0.0002359855,0.00009213122,0.000003245598],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007257717,"about_ca_system_score_gemma":0.00003960372,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004622228,"about_ca_topic_score_gemma":0.00002297702,"domain_scores_codex":[0.9993108,0.00002190657,0.0001304453,0.0002485365,0.0001502676,0.0001380752],"domain_scores_gemma":[0.9995298,0.00001959662,0.00008789855,0.0002497089,0.00008220239,0.00003074607],"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":[0.0001699951,0.000123904,0.001742604,0.000162337,0.001156158,0.0001098416,0.001218077,0.00005087152,0.9702383,0.004880661,0.008263903,0.01188338],"study_design_scores_gemma":[0.00195958,0.0014169,0.03082063,0.0005743419,0.0008988709,0.0002684353,0.03868387,0.0003405559,0.5653858,0.007433246,0.350652,0.001565714],"study_design_candidate":"bench_or_experimental","study_design_consensus":"bench_or_experimental","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9292895,0.05543345,0.001002714,0.0001236445,0.0004973385,0.000110977,0.0001170381,0.00002061679,0.01340475],"genre_scores_gemma":[0.9958578,0.001347,0.0004137795,0.00001372891,0.0001043466,2.859994e-7,0.00002777325,0.00001079745,0.002224435],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4048524,"threshold_uncertainty_score":0.4295442,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01332610608219746,"score_gpt":0.2114886873458549,"score_spread":0.1981625812636574,"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."}}