{"id":"W4391604989","doi":"10.1111/ele.14377","title":"Multi‐generation genetic contributions of immigrants reveal cryptic elevated and sex‐biased effective gene flow within a natural meta‐population","year":2024,"lang":"en","type":"article","venue":"Ecology Letters","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":5,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia","funders":"Natural Sciences and Engineering Research Council of Canada; Norges Forskningsråd; Schweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung","keywords":"Gene flow; Introgression; Immigration; Biology; Ecology; Population; Heterosis; Evolutionary biology; Sparrow; Geography; Genetic variation; Genetics; Hybrid; Demography; Gene; Sociology","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":[0.0005921273,0.0001364932,0.0001737399,0.0006658098,0.0003383815,0.0004421584,0.0002051121,0.0002359326,0.001078982],"category_scores_gemma":[0.0008767612,0.0001222028,0.0002165224,0.0004098227,0.0003925768,0.0003622142,0.0003799007,0.0003923721,0.0001616677],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002661851,"about_ca_system_score_gemma":0.0001421411,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007838476,"about_ca_topic_score_gemma":0.003414158,"domain_scores_codex":[0.9998603,0.00002717698,0.000009554439,0.00006598589,0.00002010701,0.00001691062],"domain_scores_gemma":[0.9994727,0.0001891007,0.0001105033,0.0001300099,0.00005090746,0.00004689162],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003474679,0.00008676606,0.7476308,0.00009205421,0.0004184729,0.0003215533,0.001511279,0.003119791,0.2071523,0.001523988,0.0001474078,0.03764803],"study_design_scores_gemma":[0.000006781585,0.00009372106,0.9856989,0.00001038428,0.00008361424,0.0003298544,0.0003579691,0.005986844,0.005475023,0.001160699,0.0007790442,0.00001727748],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9985208,0.00006156378,0.001085123,0.00001132721,0.000001767455,0.000001442703,0.00005295936,0.0000117853,0.0002533458],"genre_scores_gemma":[0.999323,0.00002721112,0.0004516674,0.000008209045,0.000001524617,0.000001921502,0.00006470321,0.000003413245,0.0001182842],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001078982,"threshold_uncertainty_score":0.003609598,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.00803126746054567,"score_gpt":0.2362084627504491,"score_spread":0.2281771952899035,"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."}}