{"id":"W4405726347","doi":"10.3390/genes15121637","title":"Genome-Wide Association Analysis of Growth Traits in Hu Sheep","year":2024,"lang":"en","type":"article","venue":"Genes","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":17,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Institute of Genetics; National Science and Technology Major Project; Institute of Genetics and Developmental Biology, Chinese Academy of Sciences; Chinese Academy of Sciences; China Agricultural University","keywords":"Candidate gene; Biology; Genome-wide association study; Genotyping; SNP genotyping; Breed; Genetics; Selective breeding; Genetic association; Gene; SNP; Single-nucleotide polymorphism; Biotechnology; Genotype","routes":{"ca_aff":false,"ca_fund":true,"ca_venue":false,"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":[0.0001579861,0.00008700776,0.0001501136,0.0001437214,0.0000150598,0.00001282442,0.0001116574,0.0001166374,0.00004840281],"category_scores_gemma":[0.0000626351,0.0000848333,0.0001200022,0.0004087287,0.0000189258,0.000001946624,0.00003204017,0.00004537946,0.000006310705],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000179411,"about_ca_system_score_gemma":0.00004600179,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002323098,"about_ca_topic_score_gemma":0.0001320376,"domain_scores_codex":[0.9992853,0.00003968677,0.0001923748,0.0002297987,0.0001057231,0.0001470921],"domain_scores_gemma":[0.9997384,0.00003588294,0.00004094352,0.0001111379,0.00004401979,0.00002959831],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004952467,0.0001407201,0.5768647,0.0001471163,0.002628666,0.000002701982,0.000863268,0.01134938,0.3895163,0.002867063,0.001085876,0.01448475],"study_design_scores_gemma":[0.0001013082,0.00007364613,0.9757303,0.000005702811,0.0002336778,3.201409e-7,0.00003930298,0.00006813111,0.01746813,0.0007380972,0.005433361,0.0001080271],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9900847,0.00493413,0.003050088,0.0001351092,0.0001196194,0.00007207764,0.00004848309,0.000009345415,0.001546456],"genre_scores_gemma":[0.9966879,0.0001721713,0.00208053,0.00007960349,0.0001049908,0.000009982727,0.000120643,0.00001038876,0.0007337657],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3988656,"threshold_uncertainty_score":0.3459401,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007281255387413162,"score_gpt":0.2292351128703639,"score_spread":0.2219538574829507,"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."}}