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Record W2959482529 · doi:10.4039/tce.2019.40

Effects of tebufenozide on the assemblage of moths (Lepidoptera) in an operational spruce budworm (Lepidoptera: Tortricidae) suppression programme

2019· article· en· W2959482529 on OpenAlexaffabout
Richard Westwood, D.G. Saunders, Alana R. Westwood, N. J. Holliday

Bibliographic record

VenueThe Canadian Entomologist · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect-Plant Interactions and Control
Canadian institutionsUniversity of ManitobaUniversity of Winnipeg
Fundersnot available
KeywordsTortricidaeSpruce budwormLepidoptera genitaliaChoristoneura fumiferanaBiologyPEST analysisBotanyHorticultureEcology

Abstract

fetched live from OpenAlex

Abstract Tebufenozide (Mimic) kills Lepidoptera larvae that ingest it. Aerial applications of tebufenozide were made against spruce budworm ( Choristoneura fumiferana (Clemens)) (Lepidoptera: Tortricidae) in boreal forest in Manitoba, Canada, in 1999 and 2000. In 2000 and 2001, moths in sprayed and unsprayed plots were sampled with light traps; trapping was supplemented by foliage sampling. Relative to unsprayed plots, catches of spruce budworm moths in plots sprayed in 1999 and 2000 were depressed in 2000, but not in 2001. Host tree defoliation was reduced in 2000 by 1999 and 2000 applications; the 2000 application reduced numbers of spruce budworm larvae in 2000 and 2001. Multivariate analysis revealed negative effects of tebufenozide application on two species of non-target moths in 2000 and no negative effects in 2001. Negatively affected species have larvae feeding in the tree canopy at the time of spray application. Higher catches of non-target species in sprayed treatments were observed for three species in 2000 and two species in 2001. We conclude that tebufenozide can depress the numbers of spruce budworm larvae and provide foliage protection during the year of application and the following year, and that negative effects on non-target species are detectable for about 15 months after application.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.681
Threshold uncertainty score0.802

Codex and Gemma teacher scores by category

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 head0.014
GPT teacher head0.222
Teacher spread0.208 · 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 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

Citations7
Published2019
Admission routes2
Has abstractyes

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