{"id":"W2912533719","doi":"10.1038/s41598-019-38689-2","title":"Screening for epistatic selection signatures: A simulation study","year":2019,"lang":"en","type":"article","venue":"Scientific Reports","topic":"Genetic and phenotypic traits in livestock","field":"Biochemistry, Genetics and Molecular Biology","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"","keywords":"Epistasis; Locus (genetics); Biology; Genetics; Allele; Selection (genetic algorithm); Fixation (population genetics); Evolutionary biology; Computational biology; Gene; Computer science; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"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":[0.003411571,0.0004507131,0.0007950054,0.0008648645,0.0005297786,0.0005467604,0.001147134,0.00106975,0.002016185],"category_scores_gemma":[0.009891687,0.0002801805,0.001100759,0.000928775,0.0006814243,0.0007065911,0.0006774612,0.001288379,0.0001130247],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008810284,"about_ca_system_score_gemma":0.0006396467,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.01260143,"about_ca_topic_score_gemma":0.008208742,"domain_scores_codex":[0.9991085,0.0005730225,0.0000320743,0.0001105152,0.00007084954,0.0001049918],"domain_scores_gemma":[0.9714263,0.02531586,0.0007880338,0.001096125,0.0009347216,0.0004388931],"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":[0.0004007634,0.0004791968,0.04965816,0.0000709036,0.000253719,0.0002842277,0.0001362399,0.9376538,0.002140061,0.004834191,0.0005964896,0.003492278],"study_design_scores_gemma":[0.00006181487,0.0001708286,0.003307691,0.000005834228,0.00004062393,0.00003790686,0.00006091812,0.9943916,0.000564209,0.001199386,0.0001462178,0.00001293585],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9859088,0.00006832798,0.01246491,0.0001116454,0.000008978337,0.00004338679,0.000276341,0.00005635159,0.001061242],"genre_scores_gemma":[0.9928899,0.00003223656,0.006374849,0.00002892606,0.000003941193,0.00006287695,0.0002828177,0.00001068758,0.0003139464],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01260143,"threshold_uncertainty_score":0.02505618,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0150960784160231,"score_gpt":0.2823581763198102,"score_spread":0.2672620979037871,"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."}}