{"id":"W2011862448","doi":"10.1071/an14560","title":"Genetic variation within and between subpopulations of the Australian Merino breed","year":2015,"lang":"en","type":"article","venue":"Animal Production Science","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":40,"is_retracted":false,"has_abstract":true,"ca_institutions":"Institute of Genetics","funders":"Meat and Livestock Australia","keywords":"Biology; Genetic variation; Flock; Breed; Animal science; Genetic diversity; Genetic distance; Veterinary medicine; Genetic variability; Genetics; Ecology; Genotype; Population; 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":[0.0003200795,0.00005493334,0.00005020573,0.00002385729,0.0001117931,0.00001457215,0.0001638939,0.00003317682,0.000001702447],"category_scores_gemma":[0.0001941885,0.00004217375,0.00001371162,0.0002272045,0.0004055786,0.000009139644,0.00007460317,0.00003795599,0.000001276296],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006645922,"about_ca_system_score_gemma":0.0001251532,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00004961265,"about_ca_topic_score_gemma":0.00001083652,"domain_scores_codex":[0.9993047,0.00002989785,0.0001352412,0.0002474423,0.0001828775,0.0000998845],"domain_scores_gemma":[0.999486,0.000002222288,0.00008588823,0.0002254198,0.0001425641,0.00005793246],"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":[0.00002375585,0.00002259795,0.2024832,0.000007364335,0.000009055583,1.813927e-8,0.0007341474,0.00315301,0.7898163,0.002436862,0.00024933,0.001064335],"study_design_scores_gemma":[0.00007065269,0.0001866781,0.9292078,0.000002592465,0.00001076578,0.000008781892,0.00007912093,0.00001346188,0.06890228,0.001234232,0.000231478,0.00005213767],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9981049,0.00003475395,0.0008918726,0.000416621,0.0002545372,0.0001247956,0.000002864049,0.000004169846,0.0001654304],"genre_scores_gemma":[0.9896105,9.149828e-7,0.009826019,0.00001490006,0.0001988277,0.000002768038,0.000001486817,0.000003501904,0.0003410799],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.7267246,"threshold_uncertainty_score":0.1719796,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04319135137070651,"score_gpt":0.2818008687966352,"score_spread":0.2386095174259287,"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."}}