The Impacts of Two Protein Supplements on Commercial Honey Bee ( <i>Apis mellifera</i> L.) Colonies
Bibliographic record
Abstract
Honey bees (Apis mellifera L.) are pollinators of major importance for crop production. In recent years, colony management has become more difficult due to multiple problems such as pesticide exposure, exotic parasites, pathogens and nutritional deficiencies. The latter has incited beekeepers to provide protein supplements to their colonies to make up for the lack of pollen resources in the environment. However, their efficiency varies depending on their composition and the surrounding landscape. In this field study, we provided two different protein supplements (Global Patties® and Ultra Bee®) to colonies with either limited or unlimited access to natural pollen to assess their impacts on various colony and individual bee parameters. We used 50 colonies distributed among three sites in the Montérégie area, in Quebec, Canada. We found that supplemented colonies limited in pollen collection were able to raise the same amount of brood than control colonies. Nurse bees in supplemented colonies also had a higher protein content compared to control bees. However, bees from supplemented colonies displayed shorter lifespan, which casts a doubt on the suitability of these products for honey bee nutrition. The supplement containing natural pollen, Global Patties®, was the most consumed and the most beneficial of the two for the colonies. Finally, colonies from the apiary surrounded by the highest proportion of cultivated land in a 5-km radius performed better toward the end of the season, which could be due to the presence of nutritionally interesting plants specific to the agricultural landscape at that time of the year.
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 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 | 0.001 | 0.000 |
| Open science | 0.001 | 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".