Bibliographic record
Abstract
This paper develops an integrated economic, hydrologic and GIS modeling framework to examine the cost‐effective targeting of land retirement for establishing riparian buffers in agricultural watersheds. Previous studies have examined the efficiency of targeting large land parcels for retirement or targeting management practices such as conservation tillage but have not considered narrow variable buffer strips. An empirical application of the framework in the Canagagigue Creek watershed in Ontario shows that average and marginal costs of sediment abatement increase at an increasing rate as the environmental goal becomes more stringent. The locations of the buffer strips vary across the watershed and are not necessarily located on those sites with greatest slope or those adjacent to visible streams. Cost effectiveness is further increased if the targeting is extended to allow for the width of the buffer strip to vary by location rather than assume a uniform width. The modeling results have important policy implications for the design of conservation stewardship programs such as setting appropriate environmental health goals based on marginal abatement costs relative to marginal benefits, and setting physical characteristics of the riparian buffers for selection along the drainage network in targeted sub‐catchments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".