{"id":"W4411197065","doi":"10.3168/jds.2024-26147","title":"Selection signatures in Gir and Holstein cattle","year":2025,"lang":"en","type":"article","venue":"Journal of Dairy Science","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Universidade Estadual Paulista; Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Ministério da Ciência, Tecnologia e Inovação; Empresa Brasileira de Pesquisa Agropecuária; Fundação de Amparo à Pesquisa do Estado de São Paulo; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior; Ministério da Ciência, Tecnologia, Inovações e Comunicações; Government of Canada; University of Guelph","keywords":"Selection (genetic algorithm); Holstein Cattle; Biology; Animal science; Dairy cattle; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002769196,0.0001480114,0.0002744753,0.001594144,0.0003710614,0.0004017245,0.0002098321,0.000121321,0.0003758954],"category_scores_gemma":[0.0004616094,0.00008696048,0.0001807051,0.001155118,0.0005007918,0.00007806859,0.0002937767,0.0001618545,0.00004133154],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005496885,"about_ca_system_score_gemma":0.0003439737,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.02952507,"about_ca_topic_score_gemma":0.06246737,"domain_scores_codex":[0.999607,0.0000693769,0.00002444172,0.0001213625,0.00009652921,0.000081354],"domain_scores_gemma":[0.9996862,0.00006133787,0.0001081617,0.00001902293,0.0000578873,0.00006724541],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004135103,0.00004241357,0.9495277,0.00003325715,0.0001457525,0.0004185552,0.001686962,0.0001860113,0.03221896,0.0002034912,0.00005833123,0.01506516],"study_design_scores_gemma":[0.000003724341,0.00003663239,0.9989298,0.000003629033,0.00001854102,0.0001618044,0.0002757738,0.0001254058,0.0002672051,0.00002993384,0.0001444134,0.000003057721],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995589,0.00006767042,0.00004221485,0.000003366806,4.310556e-7,0.000001783648,0.00004178408,0.000001338242,0.0002825208],"genre_scores_gemma":[0.9995209,0.00005528133,0.000133331,0.00001074441,0.000001343584,0.000002740574,0.0001681729,0.000001253692,0.0001063057],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.02952507,"threshold_uncertainty_score":0.05870646,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00621186181786545,"score_gpt":0.2555419112999697,"score_spread":0.2493300494821043,"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."}}