Comparison of the drinking water standard for pesticides of the Brazil with other countries
Bibliographic record
Abstract
The objective was to compare the types and concentrations of pesticides allowed in the water potability standard for human supply in Brazil with other countries considered to be the largest consumers of pesticides in dollars invested in purchase/trade. This is a descriptive and documentary study, with data collection in regulations available in official government websites in Brazil, USA, China, Japan, France, Germany, Canada, Argentina, India, Italy, and World Health Organization (WHO). Since Germany, France and Italy are part of the European Union (EU), the legislative resolution of the European Parliament was adopted. Pesticides number and maximum permitted values (MPV) differ between the countries and WHO. In the Brazilian ordinance there are forty pesticides, a number like the USA, Canada, China, and WHO, but that represents only 8% of the total pesticides registered for agricultural use in Brazil. When comparing the ordinance of Brazil with EU the values are only the same for Aldrin + Dieldrin. For other, amounts between 2 and 5000 times more are allowed in Brazil. Brazilian regulations do not establish a total value for the mixture of pesticides in water, only individual limits, which together can reach 1677.13 μg/L, while in EU standards it is only 0.5 μg/L. The study showed discrepancies of the pesticides allowed in water potability standard of the Brazil with other countries, but features 12 pesticides with the same concentrations as WHO guidelines, thus, a worldwide standardization in water potability regulations is necessary to promote health and reducing risk of exposure.
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.
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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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 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".