{"id":"W3125592064","doi":"10.1186/s12711-021-00602-9","title":"Expression quantitative trait loci in sheep liver and muscle contribute to variations in meat traits","year":2021,"lang":"en","type":"article","venue":"Genetics Selection Evolution","topic":"Genetic Mapping and Diversity in Plants and Animals","field":"Biochemistry, Genetics and Molecular Biology","cited_by":62,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Agriculture Victoria; National Natural Science Foundation of China; Commonwealth Scientific and Industrial Research Organisation; AgResearch; University of Alberta; Meat and Livestock Australia; China Scholarship Council; New Zealand Government","keywords":"Expression quantitative trait loci; Biology; Genome-wide association study; Quantitative trait locus; Single-nucleotide polymorphism; Genetics; Genetic association; Transcriptome; Heritability; Phenotype; Gene; Gene expression; 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":[0.0001176767,0.0001009181,0.0001107518,0.0001028827,0.00008683529,0.00002450009,0.00004715509,0.0001299134,0.00002689057],"category_scores_gemma":[0.00009796445,0.0001158946,0.00002778206,0.0002554297,0.0000185612,0.00000536765,0.00004992129,0.00007287405,0.000004637312],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00003305954,"about_ca_system_score_gemma":0.00005975352,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00008638883,"about_ca_topic_score_gemma":0.001374149,"domain_scores_codex":[0.9991122,0.0001002205,0.0001685041,0.0003217043,0.00009888103,0.0001984132],"domain_scores_gemma":[0.9996874,0.00001372245,0.00003733574,0.00006914963,0.0001228493,0.00006948174],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00005073679,0.00009464448,0.01109771,0.00001299307,0.000009308615,0.00000365595,0.0003501969,0.003980648,0.9816963,0.0004391359,0.0008757423,0.001388931],"study_design_scores_gemma":[0.001316285,0.0003580169,0.8657231,0.00004979012,0.00001892133,0.00002305787,0.0005792067,0.006972546,0.1169129,0.0004018529,0.00735272,0.0002915392],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9536238,0.001107162,0.04455096,0.0001420692,0.00007257296,0.0001564052,0.00005466827,0.000008269936,0.0002840997],"genre_scores_gemma":[0.9944128,0.0003177087,0.004747817,0.0001061968,0.00004875642,0.000009654448,0.00009227303,0.000006425457,0.0002583326],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8647833,"threshold_uncertainty_score":0.4726044,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01459706005132259,"score_gpt":0.2387418910771048,"score_spread":0.2241448310257823,"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."}}