Evaluation of the Shaking Technique for the Economic Management of American Foulbrood Disease of Honey Bees (Hymenoptera: Apidae)
Bibliographic record
Abstract
Shaking is a nonantibiotic management technique for the bacterial disease American foulbrood (AFB) (Paenibacillus larvae sensu Genersch et al.), in which infected nesting comb is destroyed and the adult honey bees, Apis mellifera L. (Hymenoptera: Apidae), are transferred onto uncontaminated nesting material. We hypothesized that colonies shaken onto frames of uninfected drawn comb would have similar reductions in AFB symptoms and bacterial spore loads than those shaken onto frames of foundation, but they would attain higher levels of production. We observed that colonies shaken onto drawn comb, or a combination of foundation and drawn comb, exhibited light transitory AFB infections, whereas colonies shaken onto frames containing only foundation failed to exhibit clinical symptoms. Furthermore, concentrations of P. larvae spores in honey and adult worker bees sampled from colonies shaken onto all comb and foundation treatments declined over time and were undetectable in adult bee samples 3 mo after shaking. In contrast, colonies that were reestablished on the original infected comb remained heavily infected resulting in consistently high levels of spores, and eventually, their death. In a subsequent experiment, production of colonies shaken onto foundation was compared with that of colonies established from package (bulk) bees or that of overwintered colonies. Economic analysis proved shaking to be 24% more profitable than using package bees. These results suggest that shaking bees onto frames of foundation in the spring is a feasible option for managing AFB in commercial beekeeping operations where antibiotic use is undesirable or prohibited.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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".