An Environmental and Economic Perspective on Integrated Weed Management in Iran
Bibliographic record
Abstract
Inputs, including herbicides, used in crop production may create negative environmental impacts. One solution to minimize these adverse effects is the adoption of integrated weed management (IWM) with the intention of reducing herbicide use. This study, conducted in 2010, estimates the willingness of farmers to pay for the adoption of more effective weed management methods. Results suggest that the willingness to pay (WTP) for IWM is greater than the WTP for other weed management methods, including chemical weed management and chemical and mechanical weed management. This study also identified a number of factors that influence the adoption of IWM on wheat farms in Iran using a multinomial logit model. Total annual income, area under irrigated wheat, wheat yield loss due to weeds, perennial nature of the weeds, and having awareness of weed resistance to herbicides had a positive effect on the adoption of IWM practices. However, having rain-fed (dryland) wheat cultivation and a larger number of plots on the farm had a negative influence on the choice of IWM.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".