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Record W4321164764 · doi:10.1093/jme/tjad014

No Effect of Realistic Microplastic Exposure on Growth and Development of Wild-caught Culex (Diptera: Culicidae) Mosquitoes

2023· article· en· W4321164764 on OpenAlexafffund
Markus Thormeyer, Michelle Tseng

Bibliographic record

VenueJournal of Medical Entomology · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyCulexMosquito controlZoologyEcologyLarvaMalariaImmunology

Abstract

fetched live from OpenAlex

Microplastic (MP) pollution is a threat to environments around the world and mosquitoes are particularly affected because of their high chance of encountering MP as larvae. Mosquitoes have been shown to readily consume microplastics and they have a significant impact on health in society, yet we have limited knowledge on the effects of MP exposure on fitness-related traits. Additionally, the data we do have come primarily from studies that have used unrealistically high microplastic concentrations, or unrealistic methods of exposure. Here we exposed wild-type first instar Culex pipiens and Culex tarsalis larvae to two 4.8-5.8 μm polystyrene microplastic concentrations (0 particles/ml, 200 particles/ml, 20,000 particles/ml) to evaluate the effect of MP exposure on body size, development, and growth rate. We found no effect of microplastics on any of the traits in either species. These results indicate microplastic exposures comparable to levels found in nature have minimal effects on these fitness-related traits. Future directions for this work include examining whether the effects of MP exposure are exacerbated when evaluated in combination with other common stressors, such as warming temperatures, pesticides, and food limitation.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.574
Threshold uncertainty score0.792

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
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 head0.008
GPT teacher head0.243
Teacher spread0.235 · 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 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

Citations17
Published2023
Admission routes2
Has abstractyes

Explore more

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