{"id":"W4221069327","doi":"10.1093/genetics/iyab229","title":"Efficient ancestry and mutation simulation with msprime 1.0","year":2021,"lang":"en","type":"article","venue":"Genetics","topic":"Gene expression and cancer classification","field":"Biochemistry, Genetics and Molecular Biology","cited_by":508,"is_retracted":false,"has_abstract":true,"ca_institutions":"McGill University","funders":"Biotechnology and Biological Sciences Research Council; Engineering and Physical Sciences Research Council; Canadian Institutes of Health Research; Directorate for Biological Sciences; National Institutes of Health; Canada Research Chairs; Deutsche Forschungsgemeinschaft; National Institute of General Medical Sciences; University of Edinburgh; Robertson Foundation; National Human Genome Research Institute; Villum Fonden","keywords":"Biology; Genetics; Mutation; Gene","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":[0.002429232,0.0009195878,0.001337348,0.0007829439,0.0007081152,0.001526398,0.003106702,0.001428348,0.0122909],"category_scores_gemma":[0.01074773,0.0008884671,0.001337651,0.0008223907,0.0006021988,0.00172845,0.001988869,0.002543583,0.005234234],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007303098,"about_ca_system_score_gemma":0.001817557,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003267732,"about_ca_topic_score_gemma":0.00398209,"domain_scores_codex":[0.9993008,0.0002199121,0.0000602091,0.0001401504,0.0002102971,0.00006863725],"domain_scores_gemma":[0.9969549,0.001973973,0.0001473356,0.0004082979,0.0003521591,0.0001633465],"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":[0.0008062709,0.0004829339,0.01876354,0.001438814,0.0007823053,0.0008880686,0.001343829,0.5535005,0.02650434,0.09483499,0.09919343,0.201461],"study_design_scores_gemma":[0.0001053225,0.00004877047,0.0007358758,0.00004511039,0.00004308192,0.0001649612,0.00004429465,0.9440296,0.007110149,0.02275035,0.02486876,0.00005371566],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.03335071,0.0003255064,0.8738125,0.000409049,0.0001821378,0.0001552619,0.003339358,0.07958379,0.008841652],"genre_scores_gemma":[0.2100045,0.0005483849,0.7533024,0.0004800752,0.00008651788,0.0008884017,0.008836273,0.01991059,0.005942849],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.0122909,"threshold_uncertainty_score":0.04111713,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01714416052983847,"score_gpt":0.2799590324191464,"score_spread":0.2628148718893079,"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."}}