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Record W4226157076 · doi:10.1093/jee/toac037

Evaluation of Standardized Bait Trapping Approaches and Climatic Factors That Influence Wireworm Catch in the Canadian Prairies

2022· article· en· W4226157076 on OpenAlexafffundabout
Ivan Drahun, Katherine A. Hunt, Willem G. van Herk, Bryan J. Cassone

Bibliographic record

VenueJournal of Economic Entomology · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicEntomopathogenic Microorganisms in Pest Control
Canadian institutionsAgriculture and Agri-Food CanadaBrandon University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyAgronomyCropWiltingAbundance (ecology)Integrated pest managementTrappingAgroforestryToxicologyEcology

Abstract

fetched live from OpenAlex

Wireworms are significant pests of a variety of economically important crops grown in the Canadian Prairies. These soil-dwelling larvae of click beetles feed on and burrow into the accessible underground plant tissues, which can result in cosmetic injury, stunting, wilting, and plant death. Successful management of wireworms relies on accurate estimations of their abundance and activity in infested fields. Bait trapping is the most commonly used method for sampling wireworms and standardized approaches have been developed; however, little work has been done to optimize trapping efficacy in different geographical regions. In this study, we evaluated the effect of bait trapping duration, seed formulation, and the causal relationship with CO2 production and soil temperature on the wireworm catch in three fields located in Manitoba, Canada. As expected, wireworm catch increased with trapping duration and placing traps in ground for 8 d is adequate in most cases. Both barley and wheat were more effective baits than soybean; however, barley released more CO2 (i.e., an attractant for wireworms) and performed better at elevated soil temperatures. Overall, the results of this study will serve as valuable guidelines to improve current wireworm sampling methods, and can be integrated into strategies aimed at managing these important pests to crop production.

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)0.005
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
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)0.0000.000

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 head0.062
GPT teacher head0.260
Teacher spread0.198 · 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

Citations5
Published2022
Admission routes3
Has abstractyes

Explore more

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