{"id":"W4377221286","doi":"10.1111/mec.16993","title":"The worldwide invasion history of a pest ambrosia beetle inferred using population genomics","year":2023,"lang":"en","type":"article","venue":"Molecular Ecology","topic":"Forest Insect Ecology and Management","field":"Environmental Science","cited_by":11,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"Animal and Plant Health Inspection Service; Région Occitanie Pyrénées-Méditerranée; U.S. Forest Service; European Commission; Centre Méditerranéen de l’Environnement et de la Biodiversité; Japan Society for the Promotion of Science; U.S. Department of Agriculture; Agence Nationale de la Recherche; National Science Foundation","keywords":"Biology; Invasive species; Ambrosia beetle; Genetic structure; Allopatric speciation; Population genomics; Ecology; Population; Introduced species; Biological dispersal; Evolutionary biology; Genetic diversity; Genetic variation; Genomics; Curculionidae; Genome; Demography; Genetics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006262945,0.0002518648,0.000320675,0.001818747,0.0003251183,0.0005190866,0.0002135601,0.0002551952,0.0005621197],"category_scores_gemma":[0.0007064682,0.0001746597,0.0003911887,0.001229132,0.0002397796,0.000381445,0.000456103,0.0003207178,0.0001138235],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002928209,"about_ca_system_score_gemma":0.0001407963,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.003474362,"about_ca_topic_score_gemma":0.007318191,"domain_scores_codex":[0.9997003,0.00005457881,0.0000183325,0.0001546469,0.00003088173,0.0000412416],"domain_scores_gemma":[0.9996616,0.0001098135,0.00009645801,0.00003565177,0.00004787863,0.00004868087],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002043274,0.00008568734,0.8839236,0.00008092477,0.0005675004,0.0003260209,0.001379309,0.002027364,0.08088782,0.0004050393,0.0002226124,0.02988971],"study_design_scores_gemma":[0.000005449042,0.00004336717,0.995242,0.00001230473,0.0001266012,0.0002103927,0.0003672268,0.002773703,0.0006121022,0.0001272945,0.0004696276,0.00001008195],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9988222,0.00007860258,0.0006620769,0.000008558344,8.384743e-7,0.00000383258,0.0001613159,0.000006377501,0.0002562193],"genre_scores_gemma":[0.9982874,0.00007064618,0.000927572,0.00001206651,0.00000242126,0.000006975813,0.0006218777,0.00000417867,0.00006690497],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.003474362,"threshold_uncertainty_score":0.006908238,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01417973146552974,"score_gpt":0.220420138505643,"score_spread":0.2062404070401133,"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."}}