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Record W2087909701 · doi:10.1603/ec11375

Residual Efficacy of Methoprene for Control of Tribolium castaneum (Coleoptera: Tenebrionidae) Larvae at Different Temperatures on Varnished Wood, Concrete, and Wheat

2012· article· en· W2087909701 on OpenAlexaff
L.K.W. Wijayaratne, Paul G. Fields, Frank H. Arthur

Bibliographic record

VenueJournal of Economic Entomology · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect Pest Control Strategies
Canadian institutionsUniversity of ManitobaAgriculture and Agri-Food Canada
FundersU.S. Department of Agriculture
KeywordsMethopreneJuvenile hormoneBiologyLarvaToxicologyResidualAnimal scienceHorticultureBotanyFood science

Abstract

fetched live from OpenAlex

The residual efficacy of the juvenile hormone analog methoprene (Diacon II) was evaluated in bioassays using larvae of Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae) exposed on unsealed concrete or varnished wood treated with a liquid formulation and held at different temperatures. When these two types of surfaces were stored at 20, 30 or 35 degrees C for 0-24 wk, the percentage of adult emergence on concrete increased with time. In contrast, there was no adult emergence from larvae exposed to varnished wood at 24 wk after treatment at any of these temperatures. The presence of flour reduced residual efficacy of methoprene on concrete, but not on varnished wood, with no differences between cleaning frequencies. Methoprene was also stable for 48 h on concrete held at 65 degrees C and wheat, Triticum aestivum L., held at 46 degrees C. Results show that methoprene is stable at a range of temperatures commonly encountered in indoor food storage facilities and at high temperatures attained during insecticidal heat treatments of structures. The residual persistence of methoprene applied to different surface substrates may be affected more by the substrate than by temperature.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

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)0.0010.000

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 head0.019
GPT teacher head0.252
Teacher spread0.233 · 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 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

Citations58
Published2012
Admission routes1
Has abstractyes

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