Quantitative weight of evidence assessment of higher-tier studies on the toxicity and risks of neonicotinoids in honeybees. 2. Imidacloprid
Bibliographic record
Abstract
A quantitative weight of evidence (QWoE) methodology was used to assess higher-tier studies on the effects of imidacloprid (IMI) on honeybees. Assessment endpoints were population size and viability of commercially managed bees and quantity of hive products. A colony-level no-observed-adverse effect concentration (NOAEC) of 25 µg IMI/kg syrup, equivalent to an oral no-observed-adverse-effect-dose of 7.3 ng/bee/d for all responses, was measured. The overall weight of evidence indicates that there is minimal risk to honeybees from exposure to IMI from its use as a seed treatment. Exposures via dusts from currently used seed coatings present a de minimis risk to honeybees when the route of exposure is via uptake in plants that are a source of pollen or nectar for honeybees. There were few higher-tier observational (ecoepidemiological) studies conducted with IMI. Considering all lines of evidence, the quality of the studies included in this analysis was variable, but the results of the studies were consistent and point to the same conclusion - that IMI had no adverse effects on viability of the honeybee colony. Thus, the overall conclusion is that IMI, as currently used as a seed treatment and with good agricultural practices, does not present a significant risk to honeybees at the level of the colony.
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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 | 0.121 | 0.239 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.011 | 0.023 |
| Bibliometrics | 0.029 | 0.011 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".