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Record W4388774495 · doi:10.1002/ps.7891

Comparing the efficacy of synthetic Varroacides and <i>Varroa destructor</i> phenotypic resistance using Apiarium and Mason jar bioassay techniques

2023· article· en· W4388774495 on OpenAlexaff
Rassol Bahreini, Cassandra Docherty, David Feindel, Samantha Muirhead

Bibliographic record

VenuePest Management Science · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsInstitute of Health EconomicsAgriculture Food and Rural DevelopmentUniversity of Alberta
Fundersnot available
KeywordsBioassayVarroa destructorBiologyResistance (ecology)BiotechnologyToxicologyBotanyGeneticsEcologyHoney Bees

Abstract

fetched live from OpenAlex

BACKGROUND: Varroa mite, Varroa destructor, is a major threat for honey bee, Apis mellifera, colonies. Beekeepers have used synthetic Varroacides against Varroa mite for decades, but resistance to organophosphates, pyrethroids and formamidine has been reported in many locations worldwide. The goals of this study were to develop a reliable bioassay to assess efficacy and phenotypic resistance to commercial Varroacides. In this study, efficacy and Varroa resistance was evaluated using the Apiarium technique in comparison to the Mason jar method. RESULTS: Among tested Varroacides, a high efficacy (89%) for Apivar was identified when compared to Bayvarol (58%), Apistan (44%) and CheckMite (6%), in a 24 h assessment. We also found that CheckMite was toxic to bees in the Mason jar method. In addition, the Apiarium technique revealed a case of phenotypic resistance to Bayvarol, Apistan and CheckMite in the mite population evaluated. CONCLUSION: A laboratory protocol was developed using the Apiarium method to evaluate Apivar efficacy. Collectively, the findings indicated that the Apiarium methodology provided a reliable technique to measure Varroacide efficacy and determine the presence of phenotypic resistance in V. destructor. © 2023 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.

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)0.001
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 score0.781
Threshold uncertainty score0.477

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
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 head0.043
GPT teacher head0.272
Teacher spread0.229 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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