Characterization of pesticide consumption in the county of Santarém, Pará, Brazil
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
Many potentially harmful pesticides for both human health and the environment are used in Brazilian Amazon. However, no scientific datum on pesticide usage is presently available for this region. Consequently, it is difficult to assess which substances arc used and in which quantities. As an important premise for future work on pesticide contamination in the county of Santarém (State of Pará, Brazil), a survey was conducted in order to qualify and quantify the use of some pesticides in this region. This investigation was made between January and March 1997 and August and October 1998 and revealed use of several organophosphates, synthetic pyrethroids and carbamates insecticides. Furthermore, many herbicides and fungicides were listed. These pesticides are used for agriculture, domestic, and sanitary programs. This paper also provides a first estimation of quantities of some insecticides commonly used in agriculture (chlorpyrifos, malathion, metamidophos and methyl-parathion). The annual consumption for these four compounds is estimated at ca. 1 910 kg. Organophosphate insecticide consumption in the county of Santarém seems to be lower than the Brazilian average in terms of «per capita» and «per agricultural area» consumptions. Nevertheless, this county uses toxic substances on sensitive environments such as floodplains (várzeas), making relevant a thorough study on the potential contamination of this environment and its biota.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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