{"id":"W2090214278","doi":"10.1111/eva.12154","title":"Joint effects of population size and isolation on genetic erosion in fragmented populations: finding fragmentation thresholds for management","year":2014,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Genetic diversity and population structure","field":"Biochemistry, Genetics and Molecular Biology","cited_by":56,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Saskatchewan","funders":"Ministerio de Ciencia e Innovación","keywords":"Biology; Population fragmentation; Habitat fragmentation; Genetic erosion; Population size; Isolation by distance; Genetic diversity; Population; Ecology; Effective population size; Endangered species; Fragmentation (computing); Small population size; Genetic variation; Inbreeding; Habitat; Genetic drift; Selection (genetic algorithm); Local adaptation; Genetic structure; Demography; Gene flow; Genetics","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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.00009523447,0.0001091072,0.0001038541,0.0001132231,0.0001536672,0.00001002789,0.0000625412,0.0001048964,0.000008721356],"category_scores_gemma":[0.00004503837,0.0001237733,0.00004334004,0.0001428273,0.0000268199,0.00001115082,0.00004029292,0.00004024411,0.000001892211],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0000314298,"about_ca_system_score_gemma":0.000005790759,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002854213,"about_ca_topic_score_gemma":0.00001711248,"domain_scores_codex":[0.9991623,0.00004819621,0.0002584292,0.0002927226,0.0001262224,0.0001121913],"domain_scores_gemma":[0.9995211,0.00004425372,0.0001369869,0.0002091141,0.00005330814,0.0000351994],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0004509847,0.0006509176,0.539941,0.001014834,0.0001203163,4.518282e-7,0.0003482124,0.08069944,0.2722764,0.07062786,0.002411496,0.03145804],"study_design_scores_gemma":[0.00091653,0.0001519996,0.9796323,0.00004193119,0.0000307261,0.000001409647,0.00003085306,0.006070235,0.001491558,0.01057855,0.000928585,0.000125332],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8626597,0.0001442364,0.1356316,0.00009825583,0.00007914003,0.001175669,0.0000234815,0.00001162808,0.0001763293],"genre_scores_gemma":[0.9669255,0.00005921794,0.03169034,0.00008832653,0.00006840886,0.0002779067,0.0007695992,0.00001052143,0.0001101848],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4396912,"threshold_uncertainty_score":0.5047328,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01048421429123268,"score_gpt":0.2492315639590902,"score_spread":0.2387473496678576,"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."}}