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Record W3163559792 · doi:10.1093/jee/toab085

Neonicotinoid Exposures that Stimulate Predatory Stink Bug, <i>Podisus maculiventris</i> (Hemiptera: Pentatomidae), Reproduction Do Not Inhibit Its Behavior

2021· article· en· W3163559792 on OpenAlexafffund
Rachel R. Rix, G. Christopher Cutler

Bibliographic record

VenueJournal of Economic Entomology · 2021
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHemiptera Insect Studies
Canadian institutionsDalhousie University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPentatomidaeBiologyPredationHormesisHeteropteraInsectToxicologyZoologyNeonicotinoidImidaclopridHouseflyReproductionBioassayPredatorPesticideEcologyMuscaLarvaEndocrinology

Abstract

fetched live from OpenAlex

Exposure to sublethal amounts of pesticide can compromise life-history traits and behavior of natural enemies thereby reducing their effectiveness as predators. However, sublethal exposures to pesticides and other stressors may also stimulate insects, a dose-response phenomenon known as hormesis. We previously reported stimulatory effects on reproduction in the beneficial insect predator Podisus maculiventris (Say) (Hemiptera: Pentatomidae) following exposure to sublethal concentrations of imidacloprid. Here we examined whether these same treatments stimulated behavior and/or predation of P. maculiventris. Stimulation of some behaviors occurred at a reproductively hormetic concentration and two additional sublethal concentrations, depending upon bioassay design and sex. We observed no substantial inhibition of behavior or predation at a reproductively hormetic concentration, demonstrating that reproductive fitness in P. maculiventris may be stimulated without compromising behaviors important in its effectiveness as a natural enemy.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
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)0.0020.000

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 head0.038
GPT teacher head0.265
Teacher spread0.227 · 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

Citations8
Published2021
Admission routes2
Has abstractyes

Explore more

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