Workshop summary: Bumble bee ecotoxicology and risk assessment
Bibliographic record
Abstract
Declines of bumble bees and other pollinator populations in Europe and North America are of concern because of their critical role for crop production and biodiversity maintenance. Although the consensus in the scientific community is that the interaction of many factors including habitat loss, forage scarcity, diseases, parasites and pesticides probably play a role in causing these declines, pesticides have received considerable public attention and scrutiny. In response regulatory agencies have introduced more stringent pollinator testing requirements for registration and re-registration of plant protection products, to ensure the risks to pollinators are minimised. Guidelines for testing bumble bees in regulatory studies are not yet available and there is a pressing need to develop suitable protocols for routine studies with these non-Apis, social bees. As a first step, Bayer CropScience, Syngenta Crop Protection and Valent U.S.A. Corporation organized a workshop bringing together a global team of bumble bee ecotoxicology experts to discuss and develop draft protocols for both semi-field (Tier II) and field (Tier III) studies. The workshop was held at the Bayer Bee Care Center, in Research Triangle Park, North Carolina during May 8-9, 2014. The participants represented academia, consulting and industry from Europe, Canada, United States and Brazil. The workshop identified a clear protection goal, and generated proposals for basic experimental layouts, relevant measurements and endpoints for both semifield (tunnel) and field tests. The workshop participants intend to disseminate this information as widely as possible to interested researchers and regulatory officers, who can advance the development of protocol guidelines based on these initial recommendations.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".