{"id":"W4385387403","doi":"10.1016/j.aqrep.2023.101689","title":"Population structure and genetic diversity of rainbow trout (Oncorhynchus mykiss) broodstocks from Brazil using SNP markers","year":2023,"lang":"en","type":"article","venue":"Aquaculture Reports","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Empresa Brasileira de Pesquisa Agropecuária; Fundação de Apoio à Pesquisa do Distrito Federal; Coordenação de Aperfeiçoamento de Pessoal de Nível Superior","keywords":"Broodstock; Rainbow trout; Biology; Genetic diversity; Genetic structure; Population; Inbreeding; UPGMA; Trout; Genetic distance; Fishery; Salmo; Zoology; Ecology; Aquaculture; Demography; Fish <Actinopterygii>","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":[0.0003643001,0.0002040431,0.000228027,0.0008357869,0.0003117869,0.00030457,0.0001815183,0.0001199447,0.0003382912],"category_scores_gemma":[0.0006203153,0.0001838845,0.0002745882,0.0005686352,0.0003311564,0.0001158818,0.0003064203,0.0001497092,0.00005900985],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006395494,"about_ca_system_score_gemma":0.0004470062,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.08943002,"about_ca_topic_score_gemma":0.2041165,"domain_scores_codex":[0.999743,0.00002654239,0.00002198996,0.0001160573,0.00005924862,0.00003307181],"domain_scores_gemma":[0.9997038,0.00004185491,0.0001072143,0.00002502295,0.00008062876,0.00004138986],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000721435,0.000026537,0.973769,0.00001782755,0.00008340325,0.00008616309,0.001572889,0.0001558547,0.01986678,0.00007771696,0.00004758069,0.004224026],"study_design_scores_gemma":[0.000003250898,0.00003041547,0.9990309,0.000005489185,0.00002451258,0.00004795167,0.00026729,0.0001686972,0.0002768802,0.00001429381,0.0001274777,0.000002876587],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996921,0.0000262284,0.00005930586,0.000004479492,4.319286e-7,0.000004086235,0.00008015119,0.000001161663,0.0001320487],"genre_scores_gemma":[0.99931,0.00004455287,0.0002327273,0.000004883337,6.077865e-7,0.000007970852,0.000278041,0.000001610358,0.0001195742],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.08943002,"threshold_uncertainty_score":0.177819,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01323627121232647,"score_gpt":0.2532034767213179,"score_spread":0.2399672055089915,"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."}}