{"id":"W4283011294","doi":"10.3389/fgene.2022.862838","title":"Genetic Characterization and Population Connectedness of North American and European Dairy Goats","year":2022,"lang":"en","type":"article","venue":"Frontiers in Genetics","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":"Forschungsinstitut für biologischen Landbau; Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement; Ministry of Agriculture, Food and Rural Affairs; Berner Fachhochschule; Ontario Ministry of Agriculture, Food and Rural Affairs; Ontario Agri-Food Innovation Alliance; European Commission; University of Bern","keywords":"Biology; Population; Context (archaeology); Genetic diversity; Breed; Livestock; Biotechnology; Genetics; Demography; Ecology","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":[0.0008557768,0.000172795,0.000214161,0.002380796,0.0003937657,0.0005392868,0.0003182182,0.0002333636,0.0007194689],"category_scores_gemma":[0.001171514,0.00009357451,0.0003061812,0.001073464,0.0006081533,0.0002530623,0.0005260141,0.0001409922,0.000079044],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004108086,"about_ca_system_score_gemma":0.0002614429,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01635031,"about_ca_topic_score_gemma":0.02609213,"domain_scores_codex":[0.9995211,0.0001064722,0.00003482729,0.0001987118,0.0000767269,0.00006214968],"domain_scores_gemma":[0.9992734,0.0002214411,0.0002115576,0.00006671497,0.0001509881,0.00007590493],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002456717,0.00005644896,0.9800053,0.00001665109,0.0001747541,0.0002863704,0.00272013,0.0002999356,0.007981618,0.0002254088,0.0000587193,0.007928963],"study_design_scores_gemma":[0.000002884018,0.0000208776,0.9991198,0.000002947594,0.00001437478,0.000102869,0.0003443921,0.0001367727,0.00007919955,0.00002440075,0.0001489179,0.000002451708],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9995571,0.00004080534,0.00009444753,0.000004326298,4.142789e-7,0.00000285339,0.00004497749,0.000001036365,0.0002541816],"genre_scores_gemma":[0.9991327,0.00006614697,0.000251219,0.00000943603,0.000003153553,0.00001089423,0.0003435372,0.000002279318,0.0001807333],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01635031,"threshold_uncertainty_score":0.03251028,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.005094279012628116,"score_gpt":0.1936803952130355,"score_spread":0.1885861162004074,"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."}}