Estimated exposure to glyphosate in humans via environmental, occupational, and dietary pathways: an updated review of the scientific literature
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.000 | 0.000 |
| 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 it