{"id":"W1987724561","doi":"10.3168/jds.2010-3308","title":"Rates of inbreeding and genetic diversity in Canadian Holstein and Jersey cattle","year":2011,"lang":"en","type":"article","venue":"Journal of Dairy Science","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":108,"is_retracted":false,"has_abstract":true,"ca_institutions":"Agriculture and Agri-Food Canada; L'Alliance Boviteq; University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada; DairyGen Council of Canadian Dairy Network","keywords":"Inbreeding; Pedigree chart; Biology; Genetic diversity; Effective population size; Population; Selection (genetic algorithm); Population size; Small population size; Dairy cattle; Animal science; Genetics; Demography; Ecology; Gene","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0002440373,0.0000436256,0.00007177348,0.00009733189,0.00006911222,0.000006730794,0.000168706,0.00003119712,0.000004975097],"category_scores_gemma":[0.00006433047,0.00003832159,0.00001172951,0.00008940088,0.0004226288,0.000009075555,0.0001115378,0.00004918449,1.348192e-7],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009496473,"about_ca_system_score_gemma":0.0002384018,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005089466,"about_ca_topic_score_gemma":0.005985437,"domain_scores_codex":[0.9995585,0.00001217156,0.0001209542,0.0000932645,0.00008504135,0.0001300638],"domain_scores_gemma":[0.999644,0.000005439492,0.00007729366,0.00006260064,0.00006004371,0.0001505539],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002181834,0.00001509652,0.9305141,0.000008782746,0.000005830665,0.000002991612,0.001383777,0.00003297976,0.06588444,0.000244134,0.00005010925,0.001835952],"study_design_scores_gemma":[0.0001907642,0.0002746573,0.9808176,0.00001383888,0.000005246707,0.00005468568,0.0002846493,0.000006248445,0.01780977,0.0004471852,0.00005059966,0.00004482066],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9986534,0.0005526707,0.0001192103,0.00002426534,0.00008025756,0.00002706573,0.000002498048,2.53106e-7,0.0005403898],"genre_scores_gemma":[0.9917884,0.00004086254,0.00809947,0.00002976691,0.00002171028,1.089733e-7,1.075261e-7,0.000001626197,0.0000179822],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.05030345,"threshold_uncertainty_score":0.7693785,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02899462736154483,"score_gpt":0.2429019868117352,"score_spread":0.2139073594501904,"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."}}