{"id":"W1755797074","doi":"10.1186/s12859-015-0581-5","title":"GENLIB: an R package for the analysis of genealogical data","year":2015,"lang":"en","type":"article","venue":"BMC Bioinformatics","topic":"Genetic Associations and Epidemiology","field":"Biochemistry, Genetics and Molecular Biology","cited_by":24,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Ottawa; Université du Québec à Chicoutimi; Université de Montréal; Centre Hospitalier Universitaire Sainte-Justine","funders":"Canadian Institutes of Health Research","keywords":"Pedigree chart; Kinship; Population; Inbreeding; Genealogy; Sample (material); R package; Software; Computer science; Flexibility (engineering); Genetic genealogy; Selection (genetic algorithm); Data science; Biology; Genetics; Demography; Artificial intelligence; Statistics; Mathematics","routes":{"ca_aff":true,"ca_fund":true,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009894278,0.0000854974,0.0001970739,0.00004184986,0.00005751336,0.00001271095,0.0005406078,0.0001308368,0.000005294599],"category_scores_gemma":[0.0007027887,0.00005506563,0.00009806968,0.0001713943,0.00007275082,0.000006124905,0.0002122163,0.00003347127,0.000003527905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000006578331,"about_ca_system_score_gemma":0.0001057403,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001791432,"about_ca_topic_score_gemma":0.0001755412,"domain_scores_codex":[0.9991853,0.00005252682,0.0003675145,0.000131793,0.00009453428,0.0001683693],"domain_scores_gemma":[0.9984971,0.00008970877,0.0002041342,0.0009932517,0.0001375343,0.00007821955],"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":[0.0005218325,0.0007306902,0.6250725,0.0002222176,0.00803149,6.044364e-7,0.002921443,0.0912556,0.00514813,0.00320894,0.2055631,0.05732344],"study_design_scores_gemma":[0.0004607302,0.0002680122,0.06840006,0.000001078389,0.0007717344,0.000002029697,0.001299449,0.9017233,0.000271739,0.0001598337,0.02649465,0.0001473798],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1694682,0.0003814416,0.8286319,0.0001213842,0.0001096228,0.0002558677,0.0006649938,0.000008715096,0.0003578153],"genre_scores_gemma":[0.60703,0.0001562692,0.3855287,0.0006215085,0.0002134804,0.00002894866,0.006228541,0.00001433446,0.0001782042],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.8104677,"threshold_uncertainty_score":0.2245511,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1554890731997377,"score_gpt":0.3560723914392484,"score_spread":0.2005833182395107,"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."}}