Improving Maize Production and Farmers’ Income Using System Dynamics Model
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
Maize demand for feed, industry, and consumption is increasing in line with the increase in population and industry, while the supply of maize does not meet the demand. Therefore, it is necessary to identify the significant variables that affect maize cultivation and scenarios to increase maize production and farmers’ income using simulation model. As a method to develop the models, a system dynamics simulation model is used to accommodate internal and external variables that affect the production and farmers’ income which can be done using organic fertilizer, the integration between land expansion and organic fertilizer, and the implementation of precision agriculture. The simulation results show that land area, use of fertilizers, and technology adoption affect the production and income of maize farmers. The scenarios developed include organic fertilizer scenario, expansion and organic fertilizer scenario, and precision agriculture scenario. The resulting scenario can be used as a recommendation for the government and stakeholders in developing strategies and policies related to a sustainable maize farming system that can help increase the production and income of maize farmers.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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