{"id":"W2017532417","doi":"10.1371/journal.pone.0115774","title":"Testing DNA Barcode Performance in 1000 Species of European Lepidoptera: Large Geographic Distances Have Small Genetic Impacts","year":2014,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Lepidoptera: Biology and Taxonomy","field":"Biochemistry, Genetics and Molecular Biology","cited_by":179,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph","funders":"Ontario Ministry of Research and Innovation; Genome Canada; Suomen Kulttuurirahasto; Ontario Genomics; Koneen Säätiö; Ontario Genomics Institute","keywords":"DNA barcoding; Biology; Intraspecific competition; Lepidoptera genitalia; Barcode; Wolbachia; Introgression; Biological dispersal; Genetic divergence; Zoology; Ecology; Disjunct; Sympatric speciation; Phylogeography; Evolutionary biology; Phylogenetic tree; Genetic diversity; Genetics; Population","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":[0.0003392893,0.0001868582,0.0002625771,0.0000803226,0.00006859801,0.00001475885,0.0002536552,0.00009438449,0.0000207247],"category_scores_gemma":[0.0002289037,0.0001711847,0.0000605933,0.00009727779,0.0001468164,0.000006708718,0.0001197942,0.0001368297,0.00001764859],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000007965727,"about_ca_system_score_gemma":0.00002394466,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00001753899,"about_ca_topic_score_gemma":0.0001587137,"domain_scores_codex":[0.9986811,0.0001730447,0.000333137,0.0003386525,0.00009224347,0.0003818679],"domain_scores_gemma":[0.9992541,0.00005293922,0.0001928452,0.0003454363,0.00007998734,0.0000746704],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00004989573,0.0003753596,0.8978929,0.0001221656,0.00007530042,0.000003065152,0.00005569901,0.00001894425,0.09766655,0.00002419884,0.000003247364,0.003712703],"study_design_scores_gemma":[0.0008073333,0.0006440003,0.8566713,0.0002882776,0.00004632249,0.000003146901,0.00003684775,0.0003222274,0.1359279,0.00001862296,0.004909715,0.0003243078],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.923087,0.0005508763,0.000176184,0.00004985879,0.00002819886,0.0001466322,0.0000154839,0.00001325001,0.07593252],"genre_scores_gemma":[0.9968157,0.0002400818,0.002276334,0.0001457552,0.0002718622,0.0000136898,0.00005328627,0.00001912226,0.0001641159],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0757684,"threshold_uncertainty_score":0.6980709,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02829736859463235,"score_gpt":0.2009391603168244,"score_spread":0.1726417917221921,"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."}}