{"id":"W2530201237","doi":"10.1371/journal.pone.0161449","title":"A DNA Barcode Library for North American Pyraustinae (Lepidoptera: Pyraloidea: Crambidae)","year":2016,"lang":"en","type":"article","venue":"PLoS ONE","topic":"Lepidoptera: Biology and Taxonomy","field":"Biochemistry, Genetics and Molecular Biology","cited_by":28,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Guelph; Agriculture and Agri-Food Canada","funders":"Agriculture and Agri-Food Canada; Smithsonian Tropical Research Institute; Washington State University; National Natural Science Foundation of China; Ontario Genomics Institute; Natural Science Foundation of Shaanxi Province; Canada Research Chairs; Ontario Genomics; Genome Canada; Washington State Department of Agriculture; Ministry of Science and Technology of the People's Republic of China; College of Charleston; York University; Natural Sciences and Engineering Research Council of Canada; Smithsonian Institution","keywords":"DNA barcoding; Barcode; Biology; Intraspecific competition; Evolutionary biology; Species complex; Taxonomy (biology); Zoology; Phylogenetic tree; Genetics; Gene","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":[0.0000665884,0.0002286499,0.0002999241,0.00004813141,0.00009491593,0.0000215079,0.0002891008,0.0001148127,0.00007181113],"category_scores_gemma":[0.0001657221,0.0001684339,0.0001260626,0.00009480932,0.000269985,0.00001612951,0.0001442376,0.00007889762,0.0001087944],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001111904,"about_ca_system_score_gemma":0.00007024563,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.000009558636,"about_ca_topic_score_gemma":0.00005254281,"domain_scores_codex":[0.9986454,0.00005432776,0.0002537875,0.00051477,0.00008791135,0.0004437531],"domain_scores_gemma":[0.9991238,0.00008129056,0.0001342409,0.000446374,0.0000660614,0.0001482722],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"bench_or_experimental","study_design_scores_codex":[0.0009648,0.001489705,0.5871402,0.0001271555,0.00103392,0.00001206527,0.0000431885,9.561232e-7,0.2572351,0.0002187743,0.004381165,0.147353],"study_design_scores_gemma":[0.002565942,0.002382405,0.03879462,0.0001570086,0.0002390283,0.000006774319,0.00002795016,0.00002479107,0.638374,0.000268375,0.3161249,0.001034144],"study_design_candidate":"bench_or_experimental","study_design_consensus":null,"genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9863041,0.0001616357,0.001184876,0.002769608,0.00006357556,0.000462465,0.0002420408,0.00007792455,0.008733762],"genre_scores_gemma":[0.9867383,0.0002202258,0.007511924,0.001491329,0.0007515604,0.0002465855,0.0002826829,0.00004330487,0.002714107],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.5483456,"threshold_uncertainty_score":0.6868533,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.02307983797628199,"score_gpt":0.2130539069977044,"score_spread":0.1899740690214224,"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."}}