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Record W3105143544 · doi:10.1111/jvec.12399

Molecular relationships of introduced<i>Aedes japonicus</i>(Diptera: Culicidae) populations in British Columbia, Canada using mitochondrial DNA

2020· article· en· W3105143544 on OpenAlexafffundabout
Iman Baharmand, Heather Coatsworth, Daniel A.H. Peach, Peter Belton, Carl Lowenberger

Bibliographic record

VenueJournal of Vector Ecology · 2020
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyPhylogenetic treeMitochondrial DNADNA barcodingAedesEvolutionary biologyGenePhylogeographyZoologyGeneticsEcologyLarva

Abstract

fetched live from OpenAlex

Aedes japonicus japonicus (Theobald) is a relatively recent immigrant to the Pacific Northwest, having been collected in Washington State in 2001 and in British Columbia (BC) since 2014. We applied a molecular barcoding approach to determine the phylogenetic relationship of Ae. j. japonicus populations in BC with those from around the world. We sequenced a 617 base-pair segment of the cytochrome c oxidase 1 gene and a 330 base-pair region of the NADH dehydrogenase 4 gene to find genetic variation and characterize phylogenetic and haplotypic relationships based on nucleotide divergences. Our results revealed low genetic diversity in the BC samples, suggesting that these populations arose from the same introduction event. However, our approach lacked the granularity to identify the exact country of origin of the Ae. j. japonicus collected in BC. Future efforts should focus on detecting and preventing new Ae. j. japonicus introductions, recognizing that current molecular techniques are unable to pin-point the precise source of an introduction.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.128
Threshold uncertainty score0.257

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.258
Teacher spread0.230 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2020
Admission routes3
Has abstractyes

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