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Record W1986101783 · doi:10.4039/n10-032

Is soybean oil an effective repellent against <i>Aedes aegypti</i>?

2010· article· en· W1986101783 on OpenAlexafffund
Cory Campbell, Gerhard Gries

Bibliographic record

VenueThe Canadian Entomologist · 2010
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pest Control Strategies
Canadian institutionsSimon Fraser University
FundersSimon Fraser UniversityNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsDEETAedes aegyptiInsect repellentToxicologyActive ingredientAedesBiologyTraditional medicineVeterinary medicineMedicineDengue feverLarvaVirologyBotanyEcologyPharmacology

Abstract

fetched live from OpenAlex

Abstract Soybean oil (SO) is considered an active ingredient in commercial BiteBlocker™ insect-repellent products. Our objective was to test mechanisms by which SO exhibits repellency, using the yellow fever mosquito, Aedes aegypti (L.) (Diptera: Culicidae), as a representative blood-feeding insect. In dual-port glass-cage olfactometers, human hands treated with SO at various concentrations attracted as many mosquitoes as did untreated hands, indicating that SO has no long-range repellent effect. In contrast, hands treated with N,N-diethyl-3-methylbenzamide (DEET) attracted significantly fewer mosquitoes than did untreated control hands. In cage experiments, treating an area of a human forearm exposed to A. aegypti with SO provided no protection against bites, whereas treating it with DEET did. These results indicate that SO has no short-range or contact repellent properties. Both DEET and the BiteBlocker™ product conferred protection for periods similar to those previously reported. Based on our data, classification of SO as an active mosquito repellent should be reconsidered.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.007

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)0.0010.000

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 head0.015
GPT teacher head0.226
Teacher spread0.211 · 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 designBench or experimental
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

Citations11
Published2010
Admission routes2
Has abstractyes

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