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Record W1976853749 · doi:10.4039/tce.2013.68

Honey production of honey bee (Hymenoptera: Apidae) colonies with high and low <i>Varroa destructor</i> (Acari: Varroidae) infestation rates in eastern Canada

2013· article· en· W1976853749 on OpenAlexafffundabout
Berna Emsen, Ernesto Guzmán‐Novoa, Paul G. Kelly

Bibliographic record

VenueThe Canadian Entomologist · 2013
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicInsect and Pesticide Research
Canadian institutionsUniversity of Guelph
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsVarroa destructorMiteBiologyVarroaInfestationVarroa sensitive hygieneApidaeHoney beeAcariVeterinary medicinePopulationHymenopteraBotanyHorticultureToxicologyMedicine

Abstract

fetched live from OpenAlex

Abstract The objective of this study was to compare the honey yields of groups of honey bee (Hymenoptera: Apidae) colonies with high and low infestation rates of the mite Varroa destructor Anderson and Trueman (Acari: Varroidae). More than 150 colonies were screened for mite fall in early spring and again 16 weeks later. The 10 colonies with the lowest rates (L) and the 10 colonies with the highest rates (H) of mite population growth were selected. These 20 colonies were evaluated for mite infestation in adult bees and honey production. Adult bee infestation in the colonies of the H group was significantly higher than in the colonies of the L group. Additionally, H and L colonies differed significantly for honey production. L colonies produced 28.91 ± 2.34 kg of honey per hive versus 18.49 ± 0.77 kg for the group of H colonies. Furthermore, the mite infestation level of colonies measured as mite fall or as number of mites per 100 bees, was significantly correlated with honey production ( r = −0.62, P &lt; 0.05 and r = −0.76, P &lt; 0.01, respectively). These results indicate that varroa mite populations significantly reduce honey yields in honey bee colonies in eastern Canada.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.211

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 head0.013
GPT teacher head0.209
Teacher spread0.196 · 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

Citations35
Published2013
Admission routes3
Has abstractyes

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