GLYPHOSATE (N-(PHOSPHONOMETHYL)GLYCINE) CONCENTRATIONS IN WATER COURSES – SYSTEMATIC REVIEW AND SCIENTOMETRIC ANALYSIS
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, which degrades into aminomethylphosphonic acid (AMPA), is the most widely used active ingredient in herbicides worldwide. Both compounds can enter aquatic systems through surface runoff, leaching, spray drift, and irrigation, leading to water contamination and subsequent incorporation into the food chain. This study aimed to perform a systematic review and scientometric analysis of research published between 2015 and 2025 on glyphosate and AMPA concentrations in surface and groundwater, and to compare geographically detected concentrations with national regulatory thresholds. A systematic review was conducted following the PRISMA protocol, complemented by scientometric analysis. Literature searches were performed in the Web of Science, PubMed, ScienceDirect, and SciELO databases. A total of 127 articles reporting glyphosate and AMPA concentrations in surface and groundwater were selected. The countries contributing the largest number of studies were Argentina, Brazil, Canada, the United States, Mexico, and Italy. Scientometric analysis revealed that these nations not only dominate research output but also constitute the most influential co-citation networks, with the most frequently cited study originating from the United States. The highest concentration reported was in Brazil (8,700 µg/L), which is 133 times above the Brazilian regulatory limit (65 µg/L). Statistical analyses further showed that glyphosate concentrations vary significantly by geographic region, with notable differences between Europe and North America. Glyphosate concentrations frequently exceed national maximum permissible limits, even in countries with stringent legislation such as those in Europe, where values surpassed the legal threshold of 0.1 µg/L at multiple sites. These findings underscore the widespread nature of glyphosate contamination and highlight the need for stronger monitoring and regulatory enforcement.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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