{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0007754365,0.0002064282,0.0003288877,0.0008616471,0.0005388673,0.0003576715,0.0002498642,0.0001865273,0.001043431],"category_scores_gemma":[0.001102055,0.0002000028,0.0002529885,0.0005150278,0.0003853607,0.0002358912,0.0005642537,0.0002254011,0.0001392404],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003645663,"about_ca_system_score_gemma":0.0002298827,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01281708,"about_ca_topic_score_gemma":0.02968347,"domain_scores_codex":[0.9996333,0.00007880616,0.00002619801,0.0001461717,0.00007936882,0.00003613243],"domain_scores_gemma":[0.999488,0.0001323124,0.0001248172,0.00009381657,0.00008073499,0.00008023577],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0005418356,0.0001213851,0.9038315,0.00005240176,0.0002323564,0.0006019023,0.009326567,0.000892572,0.06575419,0.0006464725,0.0002080072,0.01779081],"study_design_scores_gemma":[0.000003296843,0.00005505351,0.9986375,0.000003784727,0.00001761773,0.00008642847,0.0002326004,0.0004168567,0.0002097857,0.0000500202,0.0002823196,0.000004800298],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9996151,0.00001764785,0.0001088017,0.000004171438,4.802424e-7,0.000003985884,0.00004023642,0.00000179741,0.0002077327],"genre_scores_gemma":[0.9991274,0.000018183,0.0003021269,0.000004042878,9.338173e-7,0.00000774309,0.0001376872,0.000003065907,0.0003987541],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01281708,"threshold_uncertainty_score":0.02548498,"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."}}