{"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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.001032715,0.0001480971,0.0002980334,0.001585958,0.000343408,0.0008116157,0.000230823,0.0002770664,0.0008456942],"category_scores_gemma":[0.001987048,0.0001017229,0.0002143007,0.002856667,0.0007886461,0.0006701988,0.0004052714,0.0002494203,0.0001027905],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004109202,"about_ca_system_score_gemma":0.000383502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.002911575,"about_ca_topic_score_gemma":0.004919342,"domain_scores_codex":[0.99953,0.0002146324,0.00003431885,0.0001065096,0.00007759323,0.00003704265],"domain_scores_gemma":[0.9990995,0.0004161636,0.0003127873,0.000049883,0.0000797424,0.0000419605],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0003383048,0.00007388338,0.6573092,0.002510892,0.001124199,0.001707623,0.004697626,0.01202409,0.01304913,0.05228168,0.001287544,0.2535958],"study_design_scores_gemma":[0.00002283793,0.0001473774,0.9241453,0.000357196,0.0004027529,0.001126112,0.00169805,0.003929096,0.001835029,0.04689571,0.01937879,0.00006185759],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9354445,0.0462576,0.008520324,0.001170233,0.00005309348,0.00003548597,0.000324352,0.00003478271,0.008159582],"genre_scores_gemma":[0.9808134,0.01557559,0.002441018,0.0001609831,0.00007082996,0.00001761054,0.0002302515,0.000007521938,0.0006827302],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.002911575,"threshold_uncertainty_score":0.00578922,"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."}}