{"id":"W2796096269","doi":"10.1139/cjas-2017-0192","title":"Genomic retained heterosis effects on fertility and lifetime productivity in beef heifers","year":2018,"lang":"en","type":"article","venue":"Canadian Journal of Animal Science","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":22,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; Congress of Aboriginal Peoples; Alberta Livestock and Meat Agency; Alberta Crop Industry Development Fund; Agriculture Food and Rural Development","funders":"Alberta Agriculture and Forestry; Genome Alberta; Agriculture and Agri-Food Canada; Alberta Livestock and Meat Agency; Alberta Innovates; Alberta Innovates Bio Solutions","keywords":"Heterosis; Breed; Crossbreed; Biology; Animal science; Herd; Sire; Beef cattle; Loss of heterozygosity; Fertility; Productivity; Inbreeding; Biotechnology; Veterinary medicine; Genetics; Population; Agronomy; Allele; Gene; Medicine","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0004778797,0.00008006074,0.00009921817,0.00009528209,0.0001086436,0.0000325385,0.0002332476,0.00004516172,0.000004687506],"category_scores_gemma":[0.0002663217,0.00007078621,0.00002420335,0.0001432772,0.000659879,0.000008873179,0.00002495371,0.00008960137,0.000001512924],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00004884322,"about_ca_system_score_gemma":0.0007260587,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003063568,"about_ca_topic_score_gemma":0.001998643,"domain_scores_codex":[0.9992362,0.00004192927,0.0001340919,0.0002261362,0.000100421,0.0002612495],"domain_scores_gemma":[0.9993289,0.000009392323,0.0000619023,0.0001359191,0.00009606926,0.0003678085],"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":[0.0001785284,0.00001323405,0.03976917,0.000006895865,0.000005367698,0.00000298543,0.0002429397,0.00001125986,0.9563294,0.0001057183,0.00007561586,0.003258904],"study_design_scores_gemma":[0.0001687763,0.00234258,0.9151253,0.00001709857,0.000003656994,0.00001630975,0.00002069224,0.000005616469,0.08168432,0.000198465,0.0003444056,0.00007277793],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9989839,0.0002085623,0.00005131064,0.0002326391,0.000161917,0.00008142156,0.000002516402,0.000001191148,0.00027654],"genre_scores_gemma":[0.9982877,0.00000211884,0.001363529,0.0001558245,0.0001729712,6.072767e-7,2.181341e-7,0.000005889312,0.00001117071],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.8753561,"threshold_uncertainty_score":0.2886578,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00951917134768157,"score_gpt":0.2274038722735734,"score_spread":0.2178847009258918,"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."}}