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Record W4390754306 · doi:10.1093/jee/toad216

Treatment of waxborne honey bee (Hymenoptera: Apidae) viruses using time, temperature, and electron-beam irradiation

2024· article· en· W4390754306 on OpenAlexafffund
Megan J. Colwell, Stephen F. Pernal, R. William Currie

Bibliographic record

VenueJournal of Economic Entomology · 2024
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsAgriculture and Agri-Food CanadaUniversity of Manitoba
FundersAgriculture and Agri-Food CanadaCanadian Bee Research Fund
KeywordsBiologyWaxVirusIrradiationHoney beeDeformed wing virusHorticultureToxicologyVeterinary medicineBotanyVirology

Abstract

fetched live from OpenAlex

Viruses are one of many serious threats to honey bee (Apis mellifera L.) health. There are many transmission routes for honey bee viruses, and there is potential for wax comb to act as a reservoir for transmission of viruses. Some work has been done on treating viruses on wax, focusing on irradiation as a potential treatment. However, irradiation is not universally available or economically viable for beekeepers in many regions. With increased colony deaths over winter beekeepers potentially risk further loss from reusing contaminated equipment from dead colonies. Here we explored the use of storage time and temperature on the reduction of waxborne virus levels from winter loss colony wax over 30 days and at -20, 5, and 20 °C. Furthermore, because irradiation has previously worked against waxborne viruses, we performed a dosage experiment with electron-beam irradiation. Winter loss wax was again used, and exposed to 10, 25, 35, and 45 kGy irradiation, including a nonirradiated transport control. Storage time decreased abundance of black queen cell virus and deformed wing virus at times equal or greater than 30 days but temperatures had no significant effect on virus levels. All irradiation doses decreased virus abundance and prevalence, yet only 35 and 45 kGy did so at a greater rate than the effect of transport alone.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.203
Threshold uncertainty score0.499

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)0.0000.000

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 head0.031
GPT teacher head0.297
Teacher spread0.267 · 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 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

Citations7
Published2024
Admission routes2
Has abstractyes

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