PRISE-PAD Fall Armyworm SMS Alert Pikot Results
Bibliographic record
Abstract
This study evaluates the effects of a pilot mobile SMS messages campaign on farmers' knowledge and management of fall armyworm (FAW), an invasive pest of maize that is threatening food security in Kenya. The farmers' participation in the SMS message system was high, with almost 60% of farmers consistently participating through the season. The majority of farmers understood most of the messages, which they found helpful, especially on how to control and prevent FAW. We find that participation in the mobile SMS messages campaigns increased farmers' knowledge about FAW, and farmers reported reduced FAW infestation and increased maize production, as a result of implementing the recommendation actions. Male farmers were more likely to be aware of FAW and knowledgeable about the integrated management of FAW than women farmers. Recommendations are made to improve the clarity of some messaging, expand the service and undertake further analysis to ensure women farmers are able to benefit equally from the PRISE alerts.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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; both teacher heads agree on what is shown here.
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".