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Record W4412947103 · doi:10.4039/tce.2025.10011

First detection of mosquito <i>Uranotaenia sapphirina</i> (Diptera: Culicidae) in New Brunswick, Canada

2025· article· en· W4412947103 on OpenAlexafffundabout
Amanda M. MacDonald, Laura V. Ferguson, Gemma M.M. Rawson, Norman F. Boyd, Stephen B. Heard

Bibliographic record

VenueThe Canadian Entomologist · 2025
Typearticle
Languageen
FieldMedicine
TopicMosquito-borne diseases and control
Canadian institutionsAcadia UniversityUniversity of New Brunswick
FundersPublic Health AgencyPublic Health Agency of Canada
KeywordsBiologyEntomologyEcologyZoologyGeography

Abstract

fetched live from OpenAlex

Abstract Climate change and other anthropogenic stressors are reshaping Earth’s biodiversity, motivating efforts to monitor changing faunal diversity. Canada is home to 80 documented species of mosquitoes, 38 of which are reported in New Brunswick. Using Centers for Disease Control and Prevention miniature CO2 light traps, three adult mosquito collection surveys were performed to encompass 43 trapping sites across New Brunswick, Canada. Study one took place from 21 July 2022 to 9 September 2022, study two took place from 29 May 2023 to 24 October 2023, and study three took place from 15 May 2024 to 19 September 2024. Among the specimens collected, a total of 18 Uranotaenia sapphirina (Osten Sacken) (Diptera: Culicidae) were identified from five separate trapping sites. This species, previously documented only in Ontario, Quebec, and Manitoba, is considered rare in Canada and is known for its specialisation in feeding on annelids rather than vertebrates. Our detection of Ur. sapphirina in New Brunswick, where it has been absent in earlier surveys, suggests a recent range expansion, possibly driven by climate change. This observation highlights the need for ongoing surveillance to monitor the impacts of environmental changes on mosquito distribution.

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)0.001
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 score0.018
Threshold uncertainty score0.131

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.007
GPT teacher head0.229
Teacher spread0.221 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

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