Pesticide Exposure Levels and Risk Assessment in Operators Involved in the Cashew Production in Côte d’Ivoire
Bibliographic record
Abstract
To assess the level of producers’ exposure and the health risk in relation to phytosanitary practices in cashew crops in C?te d’Ivoire, a descriptive longitudinal toxicological study was conducted in 2018-2019 with 76 cashew producers in the areas of Mankono, Dabakala and Bondoukou. The data collected permitted the assessment of phytosanitary risks on the health of producers according to the Quebec-IRPeQ pesticide risk indicators. Field observations translated into scenarios were used to determine the exposure levels of producers via the UK-POEM predictive model. The main active substances used were glyphosate, 2,4-D, cypermethrin, acetamiprid, lambdacyhalothrin, profenofos, imidacloprid, deltamethrin, mancozeb and metalaxyl. The risk indicators showed that 2,4-D (TRI = 1332.25; SRI = 432.98), profenofos (TRI = 2550.25; SRI = 637.56) and mancozeb (TRI = 841; SRI = 147.18) among herbicides, insecticides and fungicides respectively could have more adverse health effects after exposure. These findings translated into scenarios specifically showed high exposure of producers to herbicides, with exposure levels ranging from 1.31 mg/kg bw/day to 1.67 mg/kg bw/day, well above the acceptable operator’s exposure levels (AOEL). These health risks could be significantly reduced if the required personal protective equipment is worn. But, recommended doses of pesticides should be reconsidered, because in some cases, applicators exposure remained high despite the protective equipment.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".