{"id":"W2158376448","doi":"10.1093/bioinformatics/btp045","title":"QMSim: a large-scale genome simulator for livestock","year":2009,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":399,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Executable; Computer science; Population; Scale (ratio); Pedigree chart; Programming language; Biology; Genetics; Cartography; Geography","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":[0.001057875,0.0007405737,0.0006735374,0.000447305,0.0005473911,0.0007405279,0.002415678,0.001005373,0.01768017],"category_scores_gemma":[0.002807671,0.0005641026,0.0007690665,0.0007894905,0.0003548282,0.0009383301,0.0008894645,0.001326102,0.002447979],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007502232,"about_ca_system_score_gemma":0.001297231,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007645097,"about_ca_topic_score_gemma":0.00439309,"domain_scores_codex":[0.9997515,0.00008885522,0.000016789,0.00003162896,0.00007691523,0.00003427232],"domain_scores_gemma":[0.9989061,0.0006268608,0.00005560767,0.00009284828,0.0002005714,0.0001180072],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003208559,0.0001131822,0.003934341,0.0002910506,0.0001403764,0.0002254175,0.0002046946,0.9275572,0.004483797,0.01276943,0.02908901,0.02087056],"study_design_scores_gemma":[0.00007776424,0.00002121468,0.0002333787,0.00001017984,0.0000121603,0.00002090915,0.0000137778,0.9877837,0.001310844,0.002190436,0.008314315,0.0000112221],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.09020126,0.0005436103,0.7987743,0.0008882784,0.0003382442,0.0004364775,0.01809549,0.06377664,0.0269457],"genre_scores_gemma":[0.5454764,0.0007506418,0.4106079,0.0004990269,0.00008802974,0.001899693,0.0199645,0.009189866,0.01152398],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.01768017,"threshold_uncertainty_score":0.05914605,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01019544802522883,"score_gpt":0.2439689393708104,"score_spread":0.2337734913455816,"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."}}