{"id":"W2733800410","doi":"10.1159/000477729","title":"Guide for Current Nutrigenetic, Nutrigenomic, and Nutriepigenetic Approaches for Precision Nutrition Involving the Prevention and Management of Chronic Diseases Associated with Obesity","year":2017,"lang":"en","type":"article","venue":"Lifestyle Genomics","topic":"Nutrition, Genetics, and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":174,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"National Heart, Lung, and Blood Institute","keywords":"Epigenetics; Obesity; Psychological intervention; Bioinformatics; Precision medicine; Nutrigenomics; Biology; Medicine; Intensive care medicine; Computational biology; Gene; Genetics; Psychiatry; Endocrinology","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002803484,0.00022042,0.000229807,0.00004004794,0.000603439,0.0001118602,0.0002804355,0.000106195,7.895276e-7],"category_scores_gemma":[0.00008346193,0.0001899506,0.00009825736,0.0000247235,0.0002530433,0.00001207674,0.000184528,0.00004257359,1.82343e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00005441655,"about_ca_system_score_gemma":0.0001046049,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000005637282,"about_ca_topic_score_gemma":0.00008545513,"domain_scores_codex":[0.9987262,0.00005814624,0.0003315608,0.0004960052,0.000113545,0.0002744922],"domain_scores_gemma":[0.9987354,0.00005801946,0.0003727963,0.0005652961,0.0001444944,0.0001239573],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"observational","study_design_scores_codex":[0.01345007,0.020201,0.2232388,0.03187261,0.004900256,0.000009528578,0.001183874,0.00154764,0.2344815,0.01266119,0.01069515,0.4457584],"study_design_scores_gemma":[0.04423989,0.009782572,0.5426524,0.002987168,0.004134866,0.00002119046,0.001313753,0.009253778,0.1581533,0.04381335,0.1807958,0.002851981],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9375725,0.04708267,0.01138975,0.00009244589,0.0001455394,0.003192006,0.0004925663,0.000009593577,0.00002291655],"genre_scores_gemma":[0.949843,0.04460832,0.003449601,0.00001630051,0.0004989672,0.0007617009,0.0005628327,0.00004488154,0.0002143989],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4429064,"threshold_uncertainty_score":0.7745962,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02335727832375417,"score_gpt":0.2692181904117282,"score_spread":0.245860912087974,"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."}}