{"id":"W2116625490","doi":"10.1093/ajcn.82.3.497","title":"Metabolomics in human nutrition: opportunities and challenges","year":2005,"lang":"en","type":"review","venue":"American Journal of Clinical Nutrition","topic":"Metabolomics and Mass Spectrometry Studies","field":"Biochemistry, Genetics and Molecular Biology","cited_by":378,"is_retracted":false,"has_abstract":false,"ca_institutions":"Trinity College","funders":"National Institute of Environmental Health Sciences; Wellcome Trust","keywords":"Metabolomics; Metabolome; Metabolite; Biology; Computational biology; Metabolite profiling; Metabolic pathway; Identification (biology); Bioinformatics; Physiology; Biotechnology; Biochemistry; Metabolism","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.006973147,0.00186227,0.004296272,0.002654996,0.0007453326,0.004113321,0.002477641,0.004991959,0.00303452],"category_scores_gemma":[0.004056765,0.0007066611,0.0008477027,0.003859508,0.003107061,0.006081997,0.002382679,0.004842628,0.00243627],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001737057,"about_ca_system_score_gemma":0.002988734,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002027207,"about_ca_topic_score_gemma":0.004045141,"domain_scores_codex":[0.9989589,0.0003694539,0.0001020904,0.0001501395,0.0003513022,0.00006807358],"domain_scores_gemma":[0.9932902,0.004347878,0.0002791271,0.0001896634,0.001522805,0.0003702769],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0001923314,0.0001519787,0.0005280408,0.007326372,0.0001455733,0.0003172697,0.0001132366,0.0004822163,0.001684233,0.01275852,0.05201474,0.9242856],"study_design_scores_gemma":[0.00006110307,0.0002394037,0.001630759,0.00418686,0.0001444739,0.001739111,0.000352691,0.0006305577,0.0008250685,0.01933381,0.9707755,0.00008059776],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.00006917398,0.9959061,0.000704559,0.002337188,0.0004649089,0.000003225009,0.00000797963,0.00001136469,0.0004955091],"genre_scores_gemma":[0.0006438532,0.994942,0.001184946,0.001262158,0.001558169,0.000008956722,0.00001217452,0.000003212134,0.0003843822],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.006973147,"threshold_uncertainty_score":0.03687799,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1960419600329725,"score_gpt":0.4306141752895485,"score_spread":0.234572215256576,"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."}}