Ecological Goods and Services Survey Summary Prepared for: Lower Souris Watershed Committee
Bibliographic record
Abstract
An interview based survey of farm landowners in the south east corner of Saskatchewan was undertaken to evaluate the provision of wildlife habitat by agriculture. Producers were asked to provide management information regarding a piece of their land that was managed as a unit. Within the past ten years there has been a reduction in the conversion of remaining native land to crop land, an increase in conversion of annual crop land to perennial cover crops, an increase in the use of minimum disturbance (no-till) farming, and a decrease in the use of fire on stubble fields and sloughs. Many producers in the area often stated economic reasons for their current land use division. Even ecological reasons (productive capacity of the soil, poor cropping soil, light soil etc.) often had an economic basis. If the land was not productive enough, a management scheme with lower input costs would be adopted. This was commonly demonstrated in this survey by the conversion of marginal land to tame forages. Producers within this region seem willing to adopt farming practices that connect economic sustainability with environmental responsibility. This survey is part of an-on going study of the region.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.216 | 0.076 |
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".