Prioritize Agri-Environmental Measures of Water-Related Ecosystem Services: The Case of Mashhad
Bibliographic record
Abstract
Current structure of agricultural input consumption eventually influences bases of natural environment and ecosystem services (especially water related) from which human communities benefit. This research aims at assisting decision making and prioritizing ecosystem services and their improvement measures according to interconnection of different ecosystem services and agri-environmental schemes of improving these services with help of fuzzy analytic network process (FANP) in Mashhad plain. Results show that among water-related ecosystem services, water quality and having healthy products, are first priorities. Providing needed water for agriculture section stands in the second rank with minor difference. Third and fourth places go to soil conservation and biodiversity relatively and agricultural tourism which is categorized under cultural services is placed in the last place. Also, based on this study results, among the seven agri-environmental water-related ecosystem services improvement, integrated pest management (IPM) ranks first. The second and third priorities belong to proposed crop pattern and conservative tillage implementation.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".