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Record W2803510894 · doi:10.1017/s0007485318000330

First molecular phylogeny of<i>Agrilus</i>(Coleoptera: Buprestidae), the largest genus on Earth, with DNA barcode database for forestry pest diagnostics

2018· article· en· W2803510894 on OpenAlexaff
Ivana Kelnarová, Eduard Jendek, Vasily V. Grebennikov, Ladislav Bocák

Bibliographic record

VenueBulletin of Entomological Research · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsCanadian Food Inspection Agency
Fundersnot available
KeywordsAgrilusBiologyBuprestidaeDNA barcodingZoologyEvolutionary biologyPolyphylyEcologyPhylogenetic treeCladeGenetics

Abstract

fetched live from OpenAlex

All more than 3000 species of Agrilus beetles are phytophagous and some cause economically significant damage to trees and shrubs. Facilitated by international trade, Agrilus species regularly invade new countries and continents. This necessitates a rapid identification of Agrilus species, as the first step for subsequent protective measures. This study provides the first DNA reference library for ~100 Agrilus species from the Northern Hemisphere based on three mitochondrial markers: cox1-5' (DNA barcode fragment), cox1-3', and rrnL. All 329 Agrilus records available in the Barcode of Life Database format, including specimen images and geo data, are released through a public dataset 'Agrilus1 329' available at: dx.doi.org/10.5883/DS-AGRILUS1. All Agrilus species were identified using adult morphology and by using molecular phylogenetic trees, as well as distance- and tree-based algorithms. Most DNA-based species limits agree well with the morphology-based identification. Our results include cases of high intraspecific variability and multiple species para- and polyphyly. DNA barcoding is a powerful species identification tool in Agrilus, although it frequently fails to recover morphologically-delimited Agrilus species-group. Even though the current three-gene database covers only ~3% of the known Agrilus diversity, it contains representatives of all principal lineages from the Northern Hemisphere and represents the most extensive dataset built for DNA-delimited species identification within this genus so far. Molecular data analyses can rapidly and cost-effectively identify an unknown sample, including immature stages and/or non-native taxa, or species not yet formally named.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.299
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.032
GPT teacher head0.294
Teacher spread0.262 · 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.

Study designObservational
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

Citations52
Published2018
Admission routes1
Has abstractyes

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