Crops Rotation – the Solution of Environmental Problems (a Case Study of Prince Edward Island in Canada)
Bibliographic record
Abstract
Prince Edward Island (PEI) is well known around the world for its potato industry. While economically beneficial for PEI, potato production contributes to its environmental deterioration. This can be attributed to the high use of chemicals and fertilizers in the production, which leads to the pollution of PEI’s watercourses. In response to the environmental crisis, the PEI provincial government proposed several land use policies to mitigate the negative influence of potato production on water quality. One of the policies that is analyzed in this paper is a mandated crop rotation. The analysis of the mandatory crop rotation policy is achieved through the application of optimal control theory and dynamic programming. Findings from the co-integration model show that agriculture is most likely responsible for watercourse pollution in PEI. This provides statistical evidence that a policy aimed at water protection, specifically targeting potato land use is necessary. However the application of environmentally friendly approach (mandatory crops rotation) is positive, its negative impact on individual farms economy is evident.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.002 |
| Science and technology studies | 0.006 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".