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Record W4391959893 · doi:10.3390/life14030283

Phylogeographic Reconstruction to Trace the Source Population of Asian Giant Hornet Caught in Nanaimo in Canada and Blaine in the USA

2024· article· en· W4391959893 on OpenAlexafffundabout
A. B. Freeman, Xuhua Xia

Bibliographic record

VenueLife · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPhylogeographyPopulationGeographyBiologyEcologyPhylogenetic treeEvolutionary biologyDemography

Abstract

fetched live from OpenAlex

The Asian giant hornet, Vespa mandarinia, is an invasive species that could potentially destroy the local honeybee industry in North America. It has been observed to nest in the coastal regions of British Columbia in Canada and Washington State in the USA. What is the source population of the immigrant hornets? The identification of the source population can shed light not only on the route of immigration but also on the similarity between the native habitat and the potential new habitat in the Pacific Northwest. We analyzed mitochondrial COX1 sequences of specimens sampled from multiple populations in China, the Republic of Korea, Japan, and the Russian Far East. V. mandarinia exhibits phylogeographic patterns, forming monophyletic clades for 16 specimens from China, six specimens from the Republic of Korea, and two specimens from Japan. The two mitochondrial COX1 sequences from Nanaimo, British Columbia, are identical to the two sequences from Japan. The COX1 sequence from Blaine, Washington State, clustered with those from the Republic of Korea and is identical to one sequence from the Republic of Korea. Our geophylogeny, which allows visualization of genetic variation over time and space, provides evolutionary insights on the evolution and speciation of three closely related vespine species (V. tropica, V. soror, and V. mandarinia), with the speciation events associated with the expansion of the distribution to the north.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.187
Threshold uncertainty score0.189

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 head0.017
GPT teacher head0.185
Teacher spread0.168 · 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 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

Citations6
Published2024
Admission routes3
Has abstractyes

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