Effects of summer treatments against <i>Varroa destructor</i> on viral load and colony performance of <i>Apis mellifera</i> colonies in Eastern Canada
Bibliographic record
Abstract
Despite the use of various integrated pest management strategies to control the honey bee mite, Varroa destructor, varroosis remains the most important threat to honey bee colony health in many countries. In Canada, ineffective varroa control is linked to high winter colony losses and new treatment options, such as a summer treatment, are greatly needed. In this study, a total of 135 colonies located in 6 apiaries were submitted to one of these 3 varroa treatment strategies: (i) an Apivar® fall treatment followed by an oxalic acid (OA) treatment by dripping method; (ii) same as in (i) with a summer treatment consisting of formic acid (Formic Pro™); and (iii) same as in (i) with a summer treatment consisting of slow-release OA/glycerin pads (total of 27 g of OA/colony). Treatment efficacy and their effects on colony performance, mortality, varroa population, and the abundance of 6 viruses (acute bee paralysis virus [ABPV], black queen cell virus [BQCV], deformed wing virus variant A [DWV-A], deformed wing virus variant B [DWV-B], Israeli acute paralysis virus [IAPV], and Kashmir bee virus [KBV]) were assessed. We show that a strategy with a Formic Pro summer treatment tended to reduce the varroa infestation rate to below the economic fall threshold of 15 daily varroa drop, which reduced colony mortality significantly but did not reduce the prevalence or viral load of the 6 tested viruses at the colony level. A strategy with glycerin/OA pads reduced hive weight gain and the varroa infestation rate, but not below the fall threshold. A high prevalence of DWV-B was measured in all groups, which could be related to colony mortality.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".