Estimated exposure to glyphosate in humans via environmental, occupational, and dietary pathways: an updated review of the scientific literature
Bibliographic record
Abstract
Glyphosate is one of the most widely used herbicides in the world, but it has also been the focus of discussion and restrictions in several countries since it was declared 'probably carcinogenic to humans (Group 2A)' by the International Agency for Research on Cancer in 2015. Since that time, several regulatory agencies have reviewed the public literature and guideline studies submitted for regulatory purposes and have concluded that it is not a carcinogen, and revised acceptable daily intakes (ADIs) and the reference dose (RfD) have been published. Also, restrictions on use have been lifted in many locations. Risk assessment for any pesticide requires knowledge of exposure in humans and the environment, and this paper is an update on a previous review in 2016 and includes papers published after 2016. These exposure data for air, water, bystanders, the general public, domesticated animals, pets, and applicators were combined and compared to the revised exposure criteria published by regulatory agencies. In all cases, measured and estimated systemic exposures to glyphosate in humans and animals were less than the ADIs and the RfD. Based on this large dataset, these exposures represent a de minimis risk. © 2019 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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".