{"id":"W3144296094","doi":"10.3390/nu13041128","title":"Genomics and Personalized Nutrition","year":2021,"lang":"en","type":"article","venue":"Nutrients","topic":"Nutrition, Genetics, and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"Université Laval","funders":"","keywords":"Genomics; Nutrigenomics; Computational biology; Genome; Personal genomics; Biology; Functional genomics; Comparative genomics; Human genome; Bioinformatics; Genetics; Medicine; Gene","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":[0.00003635032,0.0000872527,0.00008049978,0.00001950243,0.00007389887,0.00002837088,0.00004921345,0.00008348544,0.00003796641],"category_scores_gemma":[0.0000398609,0.0001013911,0.00005347005,0.0000485075,0.00006310807,0.00000225442,0.00005566603,0.00003121527,0.00000811985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001038784,"about_ca_system_score_gemma":0.00005557904,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000001493653,"about_ca_topic_score_gemma":0.000002707521,"domain_scores_codex":[0.9993694,0.0000325512,0.0001013209,0.0002721497,0.00008353825,0.0001410044],"domain_scores_gemma":[0.9995612,0.000003670926,0.00002646367,0.000176526,0.0001129308,0.0001191886],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0004315962,0.001098573,0.02315595,0.0001851126,0.00007462635,0.00003260789,0.0001271891,0.000001389606,0.9510841,0.0007131313,0.02069763,0.002398077],"study_design_scores_gemma":[0.005378534,0.0001474782,0.007865806,0.00003085849,0.0000454295,0.00004932709,0.0003346082,0.00001901342,0.3981247,0.002190064,0.5855268,0.0002873368],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9889876,0.009505068,0.0003577104,0.0001773682,0.0001345236,0.0001144131,0.00006763327,0.000008964006,0.0006467147],"genre_scores_gemma":[0.9901344,0.005801585,0.001409938,0.0006284785,0.0003826544,0.00002703527,0.000607544,0.00001722242,0.0009911234],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5648292,"threshold_uncertainty_score":0.413461,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.008288732029943213,"score_gpt":0.2359730834229096,"score_spread":0.2276843513929664,"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."}}