{"id":"W2898724829","doi":"10.1016/j.theriogenology.2018.10.025","title":"State of inbreeding and genetic trends for estimated breeding values in IVF embryos and oocyte donors in the Brazilian Guzerá cattle","year":2018,"lang":"en","type":"article","venue":"Theriogenology","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":9,"is_retracted":false,"has_abstract":false,"ca_institutions":"BIO (Canada); University of Guelph","funders":"Fundação de Amparo à Pesquisa do Estado de Minas Gerais; Conselho Nacional de Desenvolvimento Científico e Tecnológico; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Inbreeding; Ice calving; Biology; Population; Animal science; Human fertilization; Pregnancy; Genetics; Demography","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001901305,0.0001287984,0.0001743302,0.00009452051,0.00005351947,0.000009954115,0.000172529,0.0001075862,0.000008662275],"category_scores_gemma":[0.00003899894,0.0001039481,0.00002234484,0.0001158694,0.0004295218,0.000002928914,0.00007945557,0.00006017597,5.744654e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000005612941,"about_ca_system_score_gemma":0.00002595592,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0001393136,"about_ca_topic_score_gemma":0.0006294205,"domain_scores_codex":[0.9991544,0.00006452866,0.0002223322,0.0002646691,0.00004425297,0.0002498428],"domain_scores_gemma":[0.9996481,0.00004104699,0.00007058663,0.0001784838,0.00003206087,0.00002974298],"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":[0.000799045,0.0001025367,0.09348181,0.00007850477,0.00009706477,0.00000206401,0.009060691,0.0004267322,0.7550861,0.000783673,0.0001746544,0.1399071],"study_design_scores_gemma":[0.001187287,0.001685588,0.9714738,0.00002217651,0.00002298909,0.0000550386,0.0004447278,0.0002891879,0.01912496,0.00503694,0.0004789536,0.0001783369],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9969782,0.00145377,0.0008035653,0.0001395285,0.00007944032,0.0001842921,0.0000189919,0.000004700055,0.0003374926],"genre_scores_gemma":[0.9919165,0.0001390983,0.0076324,0.00009365033,0.00007826505,0.0000260692,0.0000106324,0.00001580413,0.000087598],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.877992,"threshold_uncertainty_score":0.4238879,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02063292949418446,"score_gpt":0.2744306464949713,"score_spread":0.2537977170007868,"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."}}