Performance of honeybee colonies located in neonicotinoid‐treated and untreated cornfields in Quebec
Bibliographic record
Abstract
Abstract Twenty‐two honeybee (Apis mellifera) colonies were placed in four different cornfield areas in order to study the potential in situ effects of seed‐coated systemic neonicotinoid pesticides used in cornfields (Zea mays spp) on honeybee health. Two apiaries were located in two independent neonicotinoid‐treated cornfield areas and two others in two independent untreated cornfield areas used as controls. These experimental hives were extensively monitored for their performance and health traits over a period of one year. Trapped pollen was collected and microscopically identified to define the visited flowers and the amount of corn pollen collected by bees. Liquid chromatography–mass spectrometry was performed to detect pesticide residues in honeybee foragers and trapped pollen. Honeybee colonies located in neonicotinoid‐treated cornfields expressed significantly higher varroa mite loads than those in untreated cornfields. However, brood production and colony weight were less disturbed by the treatment factor. Sublethal doses of neonicotinoids were detected in the trapped corn pollen and none in bee foragers. Overall, our results show that forager bees collected 20% of corn pollen containing variable concentrations of neonicotinoids. Colonies located in treated cornfields expressed higher varroa loads and long‐term mortality than those in untreated cornfields. On the other hand, no significant differences were observed regarding the brood production and colony weight.
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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) | 0.001 | 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".