Is it time to reassess current safety standards for glyphosate-based herbicides?
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
Use of glyphosate-based herbicides (GBHs) increased ∼100-fold from 1974 to 2014. Additional increases are expected due to widespread emergence of glyphosate-resistant weeds, increased application of GBHs, and preharvest uses of GBHs as desiccants. Current safety assessments rely heavily on studies conducted over 30 years ago. We have considered information on GBH use, exposures, mechanisms of action, toxicity and epidemiology. Human exposures to glyphosate are rising, and a number of in vitro and in vivo studies challenge the basis for the current safety assessment of glyphosate and GBHs. We conclude that current safety standards for GBHs are outdated and may fail to protect public health or the environment. To improve safety standards, the following are urgently needed: (1) human biomonitoring for glyphosate and its metabolites; (2) prioritisation of glyphosate and GBHs for hazard assessments, including toxicological studies that use state-of-the-art approaches; (3) epidemiological studies, especially of occupationally exposed agricultural workers, pregnant women and their children and (4) evaluations of GBHs in commercially used formulations, recognising that herbicide mixtures likely have effects that are not predicted by studying glyphosate alone.
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 | 0.025 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it