{"id":"W2991026871","doi":"10.1093/bioinformatics/btz881","title":"SimRVSequences: an R package to simulate genetic sequence data for pedigrees","year":2019,"lang":"en","type":"article","venue":"Bioinformatics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"Canada's Michael Smith Genome Sciences Centre; Simon Fraser University","funders":"Natural Sciences and Engineering Research Council of Canada; Canadian Statistical Sciences Institute; Canadian Institutes of Health Research","keywords":"Pedigree chart; R package; Sequence (biology); Computer science; Sample (material); Data mining; Computational biology; Genetics; Biology; Programming language; 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":[0.005152772,0.002443723,0.002236932,0.001608537,0.0007448263,0.002196678,0.004516918,0.001564466,0.06192754],"category_scores_gemma":[0.02729858,0.00215302,0.003059471,0.001677329,0.0007822984,0.001670196,0.002529264,0.003411811,0.04026242],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008653636,"about_ca_system_score_gemma":0.002836407,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.006791701,"about_ca_topic_score_gemma":0.007161283,"domain_scores_codex":[0.9977319,0.001199413,0.0001722417,0.0004371513,0.0003126059,0.0001467918],"domain_scores_gemma":[0.9932822,0.004589778,0.0004493785,0.0008152003,0.0005714076,0.0002920075],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"not_applicable","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001331967,0.0001652525,0.02167472,0.0031046,0.003104292,0.0009339023,0.0008702872,0.1618474,0.004227828,0.03228918,0.6742881,0.09616254],"study_design_scores_gemma":[0.001659146,0.000245183,0.005279059,0.000690186,0.0007912078,0.001055652,0.0001692418,0.4675392,0.006103133,0.1050008,0.4111467,0.000320571],"study_design_candidate":"not_applicable","study_design_consensus":"not_applicable","genre_codex":"methods","genre_gemma":"software","genre_scores_codex":[0.01200627,0.001099799,0.6327119,0.001097574,0.000598551,0.0004302713,0.1318047,0.2127513,0.007499436],"genre_scores_gemma":[0.0972453,0.001402234,0.5689067,0.001937229,0.0003279414,0.003579728,0.1590639,0.1585964,0.008940717],"genre_candidate":"software","genre_consensus":null,"teacher_disagreement_score":0.06192754,"threshold_uncertainty_score":0.2071683,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0579715405356776,"score_gpt":0.3316623543441026,"score_spread":0.273690813808425,"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."}}