{"id":"W2014650099","doi":"10.1038/hdy.2013.99","title":"Estimating genome-wide heterozygosity: effects of demographic history and marker type","year":2013,"lang":"en","type":"article","venue":"Heredity","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":104,"is_retracted":false,"has_abstract":false,"ca_institutions":"Université de Sherbrooke; University of Alberta","funders":"Natural Sciences and Engineering Research Council of Canada; U.S. Fish and Wildlife Service; Alberta Innovates; Alberta Conservation Association; University of Alberta; Charles Engelhard Foundation; National Geographic Society","keywords":"Loss of heterozygosity; Biology; Microsatellite; Genetics; Linkage disequilibrium; Single-nucleotide polymorphism; Inbreeding; Population; Evolutionary biology; Demographic history; Genetic variation; Allele; Genotype; Gene; Demography","routes":{"ca_aff":true,"ca_fund":true,"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":[0.009150169,0.0004716738,0.0007545192,0.001088907,0.0003716684,0.0007191395,0.0006979267,0.0006689309,0.0006191517],"category_scores_gemma":[0.01378549,0.0004734866,0.0007821065,0.001004477,0.0005421969,0.0007333321,0.0005780626,0.0005161163,0.0001727826],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002532858,"about_ca_system_score_gemma":0.0002971757,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002006862,"about_ca_topic_score_gemma":0.005632898,"domain_scores_codex":[0.9968005,0.002238852,0.0001145594,0.0005780374,0.0001745568,0.00009340045],"domain_scores_gemma":[0.9845846,0.0133671,0.000801497,0.0007662454,0.0002661016,0.000214428],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003862666,0.00007800064,0.9521716,0.00005636949,0.001623926,0.0001358204,0.0001903498,0.01021676,0.01259058,0.0003307813,0.00008657705,0.02213296],"study_design_scores_gemma":[0.00004047674,0.0003110561,0.9422837,0.00001774437,0.0007719399,0.0005358256,0.0001420956,0.05004015,0.004268268,0.001312332,0.0002304788,0.00004594347],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9728204,0.0003231873,0.02627651,0.00003997822,0.000005066709,0.000009655014,0.0001833835,0.0000512806,0.0002904482],"genre_scores_gemma":[0.9896488,0.00007411277,0.009858731,0.00002192283,0.000006311643,0.00001050252,0.0002089661,0.00001921642,0.0001514692],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009150169,"threshold_uncertainty_score":0.04839128,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.007149154031740133,"score_gpt":0.1982283337106811,"score_spread":0.191079179678941,"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."}}