{"id":"W2971854642","doi":"10.1111/mec.15221","title":"Gene flow and genetic drift in urban environments","year":2019,"lang":"en","type":"article","venue":"Molecular Ecology","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":250,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"Natural Sciences and Engineering Research Council of Canada; National Science Foundation","keywords":"Biological dispersal; Urbanization; Biology; Gene flow; Genetic diversity; Population; Genetic drift; Ecology; Genetic variation; Evolutionary biology; Habitat fragmentation; Population genetics; Gene pool; Habitat; Genetics; Gene; Demography","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00004163867,0.000115454,0.0001241551,0.00005139303,0.00002516856,0.00000875388,0.0001106846,0.0002002306,0.000133294],"category_scores_gemma":[0.00001076568,0.0001299314,0.00003554696,0.0000430678,0.00004652054,0.000001708437,0.0001397075,0.00006898086,0.00006370064],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000009481242,"about_ca_system_score_gemma":0.00001725003,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000007010338,"about_ca_topic_score_gemma":0.00003001971,"domain_scores_codex":[0.9992021,0.00006472852,0.0001244927,0.000334439,0.00006920107,0.0002049829],"domain_scores_gemma":[0.9996547,0.00000385558,0.00003718164,0.0002389057,0.000007194859,0.00005820182],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00002487057,0.00002258219,0.539028,0.000006339004,0.00002504848,0.00003285542,0.00004782685,0.002079788,0.4576109,0.00003340682,0.0001868924,0.0009015179],"study_design_scores_gemma":[0.001107602,0.000230442,0.9125255,0.00000208516,0.00001435722,0.00004690922,0.00002064834,0.0002782913,0.06064148,0.0001595937,0.02475994,0.0002131333],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9982799,0.0003923392,0.0004431672,0.00008834033,0.0001536402,0.000188303,0.000007693176,0.000003287591,0.0004433827],"genre_scores_gemma":[0.9959968,0.00006495976,0.002483274,0.0006672321,0.00002754194,0.000005850765,0.00007873776,0.00001226097,0.0006633828],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3969694,"threshold_uncertainty_score":0.5298448,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.003007251619954598,"score_gpt":0.1807683824338503,"score_spread":0.1777611308138957,"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."}}