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Record W4413918934 · doi:10.4039/tce.2025.10016

Response of yellowjackets (Hymenoptera: Vespidae) to meat, fish, and a heptyl butyrate–based synthetic chemical lure

2025· article· en· W4413918934 on OpenAlexafffundabout
T. Trottier, John H. Borden

Bibliographic record

VenueThe Canadian Entomologist · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPlant and animal studies
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsHymenopteraBiologyZoologyFish <Actinopterygii>Fishery

Abstract

fetched live from OpenAlex

Abstract Catches of yellowjackets (Hymenoptera: Vespidae) in traps baited with proteinaceous baits or a heptyl butyrate–based synthetic chemical lure in British Columbia, Canada, and Rio Negro, Argentina, differed among species. In British Columbia, western yellowjackets, Vespula pensylvanica (Saussure), responded preferentially to traps baited with rotisserie chicken (Galliformes: Phasianidae) over canned chicken or canned sardines (Clupeiformes, Clupeoidei), but the synthetic chemical lure was more attractive than rotisserie chicken. Counterintuitively, when rotisserie chicken and the synthetic chemical lure were combined, catches were reduced. In British Columbia, more German yellowjackets, V. germanica Fabricius, were caught in traps baited with rotisserie chicken than with canned chicken, and in Argentina, both German and common, V. vulgaris Linnaeus, yellowjackets preferred sardine-flavoured cat (Carnivora: Felidae) food over the synthetic chemical lure. In British Columbia, northern yellowjackets, V. alascensis (Packard), showed no preference among three types of chicken or between rotisserie chicken and canned sardines. When rotisserie chicken and the synthetic chemical lure were combined, catches of both northern and German yellowjackets were no higher than when traps were baited with rotisserie chicken alone. Resolution of the differential roles of red meat-, poultry-, and fish-based baits, as well as improvement of synthetic chemical lures, would be facilitated by identification of bioactive semiochemicals.

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 score0.031
Threshold uncertainty score0.063

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.024
GPT teacher head0.219
Teacher spread0.195 · 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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