{"id":"W3125041318","doi":"10.1159/000512544","title":"Strengthening the Reporting of Nutritional Genomics Research to Inform Knowledge Translation in Personalized Nutrition","year":2021,"lang":"en","type":"editorial","venue":"Lifestyle Genomics","topic":"Nutrition, Genetics, and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institut National de la Recherche Scientifique","funders":"Canadian Institutes of Health Research","keywords":"Nutrigenomics; Genomics; Knowledge translation; Checklist; Knowledge management; Medicine; Data science; Computer science; Psychology; Biology; Genetics; Genome","routes":{"ca_aff":true,"ca_fund":true,"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":[0.002218907,0.0003023219,0.0004745933,0.0002777961,0.000245603,0.00008803737,0.0004301225,0.0007798871,0.00001481118],"category_scores_gemma":[0.003315941,0.0003193098,0.0002493317,0.0004172541,0.0001891671,0.000007937719,0.0002033489,0.0006137524,0.000007259493],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002167475,"about_ca_system_score_gemma":0.0017808,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004657374,"about_ca_topic_score_gemma":0.000355912,"domain_scores_codex":[0.9962415,0.0002878664,0.001752826,0.000650783,0.000588446,0.0004785405],"domain_scores_gemma":[0.9968659,0.0004578549,0.0007426942,0.0006075304,0.001156102,0.0001699387],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001570202,0.00136208,0.0004162574,0.001868774,0.0002270974,0.00002613912,0.004047776,0.0004496995,0.1847849,0.0001892671,0.8008147,0.004243094],"study_design_scores_gemma":[0.001770809,0.0002264107,0.00008907165,0.0003033026,0.0000480059,0.000006106317,0.001511595,0.00007056107,0.01291615,0.000299807,0.9824036,0.0003546027],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"empirical","genre_gemma":"editorial","genre_scores_codex":[0.7924458,0.03745916,0.0006441636,0.0007483345,0.1615134,0.00293569,0.002702235,0.00004485577,0.001506358],"genre_scores_gemma":[0.09026744,0.01509314,0.009516894,0.000125295,0.8622994,0.0007471229,0.02053474,0.00030045,0.001115554],"genre_candidate":"editorial","genre_consensus":null,"teacher_disagreement_score":0.7021784,"threshold_uncertainty_score":0.9999259,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.05746156402652824,"score_gpt":0.3600428129202678,"score_spread":0.3025812488937396,"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."}}