Development of Exposure Biomarkers for the Honey Bee (Apis mellifera): Neonicotinoids Versus Traditional Pesticides
Bibliographic record
Abstract
Pollination is a vital ecosystem service crucial for reproduction of flowering plants, including agricultural crops. The western honey bee, Apis mellifera, is the most used managed pollinator worldwide. The use and overuse of agrochemicals is hypothesized to have played a role in increasing rates of colony mortality in Canada and globally. The identity of stressors affecting a colony is difficult to discern; information critical for diagnosing and managing honey bee colony health. Here, I explored the potential of using gene expression profiles as diagnostic biomarkers for exposure to various agrochemicals in honey bees. I found genes differentially expressed unique to each stressor, which could be putative biomarkers for specific agrochemical exposure. I found genes common between pesticides, which could be a putative general agrochemical stress signal. My research indicates that gene expression profiles can be an excellent tool for discovering stressor-specific biomarkers and diagnosing stressors found in honey bee colonies.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".