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Record W2530201237 · doi:10.1371/journal.pone.0161449

A DNA Barcode Library for North American Pyraustinae (Lepidoptera: Pyraloidea: Crambidae)

2016· article· en· W2530201237 on OpenAlexafffund
Zhaofu Yang, Jean‐François Landry, Paul D. N. Hebert

Bibliographic record

VenuePLoS ONE · 2016
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicLepidoptera: Biology and Taxonomy
Canadian institutionsUniversity of GuelphAgriculture and Agri-Food Canada
FundersAgriculture and Agri-Food CanadaSmithsonian Tropical Research InstituteWashington State UniversityNational Natural Science Foundation of ChinaOntario Genomics InstituteNatural Science Foundation of Shaanxi ProvinceCanada Research ChairsOntario GenomicsGenome CanadaWashington State Department of AgricultureMinistry of Science and Technology of the People's Republic of ChinaCollege of CharlestonYork UniversityNatural Sciences and Engineering Research Council of CanadaSmithsonian Institution
KeywordsDNA barcodingBarcodeBiologyIntraspecific competitionEvolutionary biologySpecies complexTaxonomy (biology)ZoologyPhylogenetic treeGeneticsGene

Abstract

fetched live from OpenAlex

Although members of the crambid subfamily Pyraustinae are frequently important crop pests, their identification is often difficult because many species lack conspicuous diagnostic morphological characters. DNA barcoding employs sequence diversity in a short standardized gene region to facilitate specimen identifications and species discovery. This study provides a DNA barcode reference library for North American pyraustines based upon the analysis of 1589 sequences recovered from 137 nominal species, 87% of the fauna. Data from 125 species were barcode compliant (>500bp, <1% n), and 99 of these taxa formed a distinct cluster that was assigned to a single BIN. The other 26 species were assigned to 56 BINs, reflecting frequent cases of deep intraspecific sequence divergence and a few instances of barcode sharing, creating a total of 155 BINs. Two systems for OTU designation, ABGD and BIN, were examined to check the correspondence between current taxonomy and sequence clusters. The BIN system performed better than ABGD in delimiting closely related species, while OTU counts with ABGD were influenced by the value employed for relative gap width. Different species with low or no interspecific divergence may represent cases of unrecognized synonymy, whereas those with high intraspecific divergence require further taxonomic scrutiny as they may involve cryptic diversity. The barcode library developed in this study will also help to advance understanding of relationships among species of Pyraustinae.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.548
Threshold uncertainty score0.687

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.023
GPT teacher head0.213
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations28
Published2016
Admission routes2
Has abstractyes

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