Heightened sensitivity in high-grooming honey bees (Hymenoptera: Apidae)
Bibliographic record
Abstract
Honey bees use grooming to defend against the devastating parasite Varroa destructor Anderson and Trueman. We observed the grooming responses of individual bees from colonies previously chosen for high- and low-grooming behavior using a combination of mite mortality and mite damage. Our aim was to gain insight into specific aspects of grooming behavior to compare if high-grooming bees could discriminate between a standardized stimulus (chalk dust) and a stimulus of live Varroa mites and if bees from high-grooming colonies had greater sensitivity across different body regions than bees from low-grooming colonies. We hypothesized that individuals from high-grooming colonies would be more sensitive to both stimuli than bees from low-grooming colonies across different body regions and that bees would have a greater response to Varroa than a standardized irritant (chalk dust). Individuals from high-grooming colonies responded with longer bouts of intense grooming when either stimulus was applied to the head or thorax, compared to sham-stimulated controls, while bees from low-grooming colonies showed no differences between stimulated and sham-stimulated bees. Further, high-grooming bees from colonies with high mite damage exhibited greater grooming to Varroa than high-grooming colonies with only moderate mite damage rates. This study provides new insights into Varroa-specific aspects of grooming, showing that although a standardized stimulus (chalk dust) may be used to assess general grooming ability in individual bee grooming assays, it does not capture the same range of responses as a stimulus of Varroa. Thus, continuing to use Varroa mites in grooming assays should help select colonies with more precise sensitivity to Varroa.
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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 | 0.000 | 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) | 0.001 | 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".