Stubble burning and tillage effects on soil organic C, total N and aggregation in northeastern Saskatchewan
Bibliographic record
Abstract
BACKGROUND• Sustainable crop production is a function of soil quality, which is linked to organic matter.Crop residues are a source of soil organic matter and plant nutrients.• Zero-tillage (ZT) with standing stubble conserves soil, enhances organic matter and water in soil, and generally increases crop production.• In the Parkland region of western Canada, large quantities of straw are produced, which if left on soil surface sometimes cause management problem in seeding and depress crop yield due to poor establishment and N immobilization.• In these areas, producers often burn straw in the field to facilitate the seeding operation, and reduce crop disease and weed populations.• Burning of straw can cause a considerable loss of crop residues, and organic C, N, S and other nutrients by volatilization to the atmosphere.• Burning also causes soil desiccation, makes soil harder and less friable, reduces the potential for snow trapping or conservation, and increases water runoff and potential for soil erosion.• Long-term continuous use of this practice can result in considerable reduction in soil organic C and N and cause detrimental effects on some soil properties, and loss of productivity.• Therefore, the impact of this practice on crop yield and soil properties must be assessed.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".