{"id":"W2758550728","doi":"10.1111/eva.12559","title":"Assessing the potential of genotyping‐by‐sequencing‐derived single nucleotide polymorphisms to identify the geographic origins of intercepted gypsy moth (<i>Lymantria dispar</i>) specimens: A proof‐of‐concept study","year":2017,"lang":"en","type":"article","venue":"Evolutionary Applications","topic":"Forest Insect Ecology and Management","field":"Environmental Science","cited_by":31,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of British Columbia; Université Laval; Natural Resources Canada","funders":"Natural Sciences and Engineering Research Council of Canada","keywords":"Lymantria dispar; Gypsy moth; Subspecies; Biology; Biological dispersal; Population; Ecology; Range (aeronautics); Introgression; Genotyping; Population genetics; Introduced species; Zoology; Evolutionary biology; Lepidoptera genitalia; Genetics; Genotype; 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":[0.0004000279,0.0001581639,0.0002113954,0.00006600845,0.0009672854,0.00004552088,0.001144862,0.00005223891,0.0004298226],"category_scores_gemma":[0.00004644592,0.0001145534,0.0001107609,0.0003107674,0.001238532,0.0003172876,0.0006095758,0.0001382012,0.00003120471],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002148272,"about_ca_system_score_gemma":0.00003243385,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00178777,"about_ca_topic_score_gemma":0.0003346546,"domain_scores_codex":[0.998459,0.0001311974,0.0004816908,0.0003538858,0.000327813,0.0002463798],"domain_scores_gemma":[0.9981436,0.00008344687,0.0005848092,0.001090048,0.00004400191,0.0000541155],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"bench_or_experimental","study_design_gemma":"observational","study_design_scores_codex":[0.00008440988,0.002711258,0.0850917,0.00002852353,0.0003634935,0.000003143289,0.002741544,0.007189589,0.8863636,0.007369066,0.00371914,0.004334514],"study_design_scores_gemma":[0.0003426414,0.0001793854,0.9877605,0.00002003285,0.0001298025,0.000004668791,0.001312791,0.0006029374,0.00627981,0.001932652,0.001294977,0.0001398191],"study_design_candidate":"observational","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9764028,0.0001189454,0.01940028,0.0006944833,0.0001506803,0.002082938,0.00004736183,0.00002271136,0.001079846],"genre_scores_gemma":[0.9985988,0.00000835231,0.0008000436,0.00007678941,0.00005135611,0.000335169,0.00001574657,0.00001449943,0.00009928262],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.9026688,"threshold_uncertainty_score":0.7439675,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01820047732686663,"score_gpt":0.2813392855840053,"score_spread":0.2631388082571386,"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."}}