{"id":"W3035367124","doi":"10.1111/mec.15501","title":"Variation in recombination rate affects detection of outliers in genome scans under neutrality","year":2020,"lang":"en","type":"article","venue":"Molecular Ecology","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":109,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary; University of British Columbia","funders":"Canadian Network for Research and Innovation in Machining Technology, Natural Sciences and Engineering Research Council of Canada; Genome Canada","keywords":"Coalescent theory; Biology; Outlier; Recombination; Background selection; Gene density; Evolutionary biology; Genome; Selection (genetic algorithm); Genetic variation; Statistic; Genetic drift; Population; Genome evolution; Genetics; Statistics; Phylogenetic tree; Gene; Computer science; Mathematics","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":[0.01458608,0.0003125577,0.0008498216,0.001586119,0.0005268001,0.001761363,0.0009487176,0.001117504,0.0008297086],"category_scores_gemma":[0.0617284,0.0003424185,0.0006266002,0.001129814,0.001959667,0.001288306,0.000913337,0.001241122,0.0001416425],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004582013,"about_ca_system_score_gemma":0.0002836401,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0009783221,"about_ca_topic_score_gemma":0.0008417784,"domain_scores_codex":[0.9909762,0.005774131,0.0004888437,0.001596055,0.0008333057,0.0003315511],"domain_scores_gemma":[0.9142365,0.07221464,0.006656293,0.004384174,0.001672354,0.0008359996],"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":[0.001996597,0.0001419247,0.7805076,0.0002523601,0.001348672,0.0009095712,0.001322719,0.04890281,0.1307432,0.004853875,0.0005167163,0.02850399],"study_design_scores_gemma":[0.0001138356,0.00115638,0.6717787,0.00007116485,0.0006400238,0.002525575,0.0009292269,0.2434984,0.06082243,0.01706631,0.001178099,0.0002199445],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9748054,0.0001709408,0.02428311,0.00006803427,0.00001089828,0.000009896146,0.00009841743,0.0002096866,0.0003436505],"genre_scores_gemma":[0.9974812,0.00001640307,0.002285622,0.00002631838,0.000003977978,0.000005777876,0.0001161064,0.00003719679,0.00002752457],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.01458608,"threshold_uncertainty_score":0.07713944,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00965318590781084,"score_gpt":0.2188146161306704,"score_spread":0.2091614302228596,"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."}}