Pesticides handling practices among potato growers in Kavrepalanchok, Nepal
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
The rate of pesticide application in the agricultural field is surging. Farmers are getting exposed to pesticide hazards from the misuse and unsafe handling of pesticides. The study was conducted among 101 potato growers in Kaverpalanchok district of Nepal in 2018. The objective of the study was to assess the knowledge, status, and pesticide handling practices among potato growers. Around 94% farmers applied pesticides against early and late blight. Only 5% growers treated seed before potato sowing. About 93 and 73% farmers sprayed pesticides 2-10 times/season into the field and spent 2-6 hours/pesticide spray respectively. More than 2/3rd growers did not read the pesticide labels, and nearly 95% growers received information on pesticide applications from agrovet rather than authorized government bodies. Only 13% farmers had received Integrated Pest Management (IPM) training. However, 1/4th of them had practiced IPM techniques. The majority of the growers used masks, rubber boots, and long-sleeved clothes during pesticide handling. Nearly 2/3rd growers threw pesticide containers anywhere in the environment. Concerned authorities should provide IPM training, skill-building programs on pesticide handling and awareness on waiting period and environmental hazards to avoid pesticide risk.
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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 | 0.001 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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