Measured exposures to glyphosate in applicators and the general population: an updated review of the scientific literature since 2020
Bibliographic record
Abstract
Glyphosate is one of the most widely used herbicides in the world and its continued use in agriculture and other scenarios is the focus of intense public and scientific interest. Glyphosate is also controversial in that it was declared 'probably carcinogenic to humans (Group 2A)' by the International Agency for Research on Cancer in 2015. However, since that time, regulatory agencies in many countries have reviewed the public literature and guideline studies submitted for regulatory purposes and have concluded that it is not a carcinogen. The acceptable daily intakes (ADIs) and the reference dose (RfD) have been revised and restrictions on use have been lifted in many locations. Risk assessment for any pesticide requires information on exposure in humans and the environment and this was reviewed in 2016 and in 2020. Since 2020 many studies have been published in the literature and by government departments. Most of these studies have focused on exposures of the general population, which is the subject of this paper. Based on the studies published since 2020, the overall conclusion is that exposure of applicators and the general population to glyphosate represents a de minimis risk. In addition, a general observation from the larger population-based studies that conduct routine sampling is that exposures have declined somewhat since 2020. © 2025 The Author(s). Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".