{"id":"W199392948","doi":"10.1016/b978-0-08-088504-9.00305-6","title":"Nutrigenomics","year":2011,"lang":"en","type":"book-chapter","venue":"Elsevier eBooks","topic":"Nutrition, Genetics, and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":6,"is_retracted":false,"has_abstract":false,"ca_institutions":"University of Toronto","funders":"","keywords":"Nutrigenomics; Genomics; Disease; Medicine; Biology; Biotechnology; Computational biology; Bioinformatics; Genome; Genetics; Internal medicine","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.00008189959,0.0003964081,0.0002959082,0.0000713075,0.00008687429,0.00002446895,0.0003144663,0.0005285425,0.0002684512],"category_scores_gemma":[0.00001042759,0.0004273512,0.0003248612,0.000004067427,0.0001691524,8.545783e-7,0.0001585682,0.0001643595,0.0002123127],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002251848,"about_ca_system_score_gemma":0.0001848321,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":3.056062e-7,"about_ca_topic_score_gemma":0.00001126777,"domain_scores_codex":[0.9986723,0.00001654432,0.0003250614,0.0005661396,0.0001405501,0.0002794264],"domain_scores_gemma":[0.9986802,0.000004125523,0.0001639114,0.0007881076,0.0001327591,0.0002308556],"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":[0.0002582271,0.0000727867,0.00004386641,0.0002104175,0.0003437466,0.00003985302,0.00007646558,4.13212e-7,0.006491565,0.00894464,0.007399778,0.9761183],"study_design_scores_gemma":[0.0004291979,0.0001484473,0.00001669418,0.00005911267,0.0001199065,0.00001269917,0.000002628195,1.493713e-7,0.004282045,0.02676747,0.967665,0.0004966652],"study_design_candidate":"design_other","study_design_consensus":null,"genre_codex":"other","genre_gemma":"other","genre_scores_codex":[0.0004623877,0.008472049,0.00001842972,0.00001011718,0.0003412462,0.00037352,0.0001880604,0.00002355627,0.9901106],"genre_scores_gemma":[0.00272911,0.002540248,0.0003551822,0.0005485595,0.001439741,0.00002971506,0.0004482956,0.0001304674,0.9917787],"genre_candidate":"other","genre_consensus":"other","teacher_disagreement_score":0.9756216,"threshold_uncertainty_score":0.9998178,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0135883809314231,"score_gpt":0.2190659528078355,"score_spread":0.2054775718764124,"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."}}