{"id":"W2993257390","doi":"10.1093/jas/skz258.110","title":"52 Genomic selection in the beef industry: Current achievements and future directions","year":2019,"lang":"en","type":"article","venue":"Journal of Animal Science","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":3,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Genotyping; Biology; SNP genotyping; Runs of Homozygosity; Selection (genetic algorithm); Inbreeding; Genomic selection; SNP; Genome-wide association study; Beef cattle; Genetics; Biotechnology; Genotype; Single-nucleotide polymorphism; Population; Medicine; Gene; Computer science","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.010562,0.0005080824,0.0008290728,0.001037258,0.0005498473,0.003035928,0.001368458,0.002112533,0.00889888],"category_scores_gemma":[0.005910374,0.0001827821,0.0005604872,0.001649652,0.002286872,0.002390939,0.00151391,0.001881371,0.001493657],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001798808,"about_ca_system_score_gemma":0.003367638,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003881452,"about_ca_topic_score_gemma":0.004269011,"domain_scores_codex":[0.9982144,0.000752506,0.0001013389,0.0003297509,0.000383046,0.0002189425],"domain_scores_gemma":[0.9922521,0.00420281,0.0005313195,0.0002630832,0.001744775,0.001005857],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.0003473926,0.0001933031,0.00752817,0.001817965,0.00008703426,0.0001553183,0.0002685168,0.0009138496,0.001912578,0.01784415,0.02868679,0.940245],"study_design_scores_gemma":[0.0001239381,0.001293504,0.02381732,0.007319069,0.0002537212,0.0007426373,0.002053763,0.00293623,0.002394336,0.04927334,0.9096507,0.0001414374],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"review","genre_gemma":"review","genre_scores_codex":[0.006989886,0.9303399,0.004954088,0.04396192,0.001238197,0.00002856708,0.0001704668,0.0001299266,0.01218694],"genre_scores_gemma":[0.09358971,0.8606824,0.01468615,0.02043642,0.004385449,0.00008760295,0.0004797722,0.00006541184,0.005587104],"genre_candidate":"review","genre_consensus":"review","teacher_disagreement_score":0.010562,"threshold_uncertainty_score":0.0558579,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01026859109544612,"score_gpt":0.2679156216587761,"score_spread":0.2576470305633299,"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."}}