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Record W4312195243 · doi:10.3390/insects13121175

Use of a Sprayable Sex Pheromone Formulation in Landscape-Level Control of Choristoneura fumiferana Populations

2022· article· en· W4312195243 on OpenAlexafffund
Lucas E. Roscoe, Wayne E. MacKinnon, Jacques Régnière, Glen Forbes, Matt Brophy, Rosanna Lamb

Bibliographic record

VenueInsects · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Insect Ecology and Management
Canadian institutionsNatural Resources CanadaCanadian Forest Service
FundersAtlantic Canada Opportunities Agency
KeywordsChoristoneura fumiferanaMating disruptionBalsamBiologySpruce budwormSex pheromoneMatingToxicologyPopulationPEST analysisHectarePest controlPheromoneEcologyBotanyZoologyTortricidaeDemography

Abstract

fetched live from OpenAlex

Choristoneura fumiferana (SBW) is a major defoliating pest of balsam fir and spruce in eastern North America. As part of an integrated management strategy for SBW, we evaluated the effectiveness of mating disruption as a landscape-level population control tactic. Using a sprayable formulation (CONFOUNDSBW) containing a synthetic sex pheromone blend, we treated five 300 ha blocks in Northern New Brunswick with an aerially applied microencapsulated mixture. There were significant reductions in adult trap catches in treated blocks compared to untreated control blocks. Branch sampling in treated blocks showed uniform distribution of CONFOUNDSBW deposition throughout the blocks. Population densities following treatment were not significantly affected when compared to densities in control blocks, or prior to treatment. Analysis of egg:adult ratios indicates that no immigration events occurred within treatment or control blocks. The lack of population reduction following treatment strongly suggests that widespread application of CONFOUNDSBW at a rate of 50 g of active ingredient per hectare is not an effective tool in controlling SBW populations.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.223
Threshold uncertainty score0.999

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 head0.045
GPT teacher head0.241
Teacher spread0.197 · 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.

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

Citations4
Published2022
Admission routes2
Has abstractyes

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