{"id":"W4404869201","doi":"10.5376/gab.2024.15.0015","title":"Nutritional Genomics in Pet Animals: Interactions between Diet and Genetics","year":2024,"lang":"en","type":"article","venue":"Genomics and Applied Biology","topic":"Nutrition, Genetics, and Disease","field":"Biochemistry, Genetics and Molecular Biology","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Genomics; Genetics; Biology; Medical genetics; Computational biology; Genome; Gene","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001127045,0.0001714499,0.0001756736,0.00009801447,0.00007716718,0.00005706841,0.00008873338,0.0001197067,0.0000130463],"category_scores_gemma":[0.000007082764,0.0001806119,0.00004416765,0.00005813712,0.0001738445,0.000002160704,0.0001510237,0.0001117456,0.000006335071],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00002413145,"about_ca_system_score_gemma":0.00007124476,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000006918935,"about_ca_topic_score_gemma":0.00004304415,"domain_scores_codex":[0.9989691,0.00002599929,0.0002443542,0.0004881597,0.0000304251,0.0002420013],"domain_scores_gemma":[0.9996461,0.00003213366,0.00003263206,0.000147689,0.00002219256,0.000119237],"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":[0.0003287658,0.00009829079,0.01677622,0.000133467,0.0001233072,0.00000961826,0.0001217347,0.00002284341,0.9642698,0.007725259,0.0008682887,0.009522404],"study_design_scores_gemma":[0.003030913,0.001081249,0.06674635,0.00005048715,0.0001700911,0.0001580982,0.0006163634,0.0006349245,0.05204241,0.05710028,0.8171281,0.001240768],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9862533,0.01168386,0.0004445883,0.0002829943,0.0001272227,0.0002124375,0.0004905335,0.00001352399,0.000491556],"genre_scores_gemma":[0.9882789,0.008137403,0.001975892,0.0001879373,0.0006744079,0.00004316046,0.0006433553,0.00002439545,0.00003456364],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9122274,"threshold_uncertainty_score":0.7365138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01296838258807741,"score_gpt":0.2656003234618246,"score_spread":0.2526319408737471,"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."}}