Can the quality of soil structure be maintained following repeated applications of high rates of hog manure
Bibliographic record
Abstract
The long-term impact of repeated applications of high rates of liquid hog manure on the quality of the soil and that of the environment is not well known. For optimal application rates of hog manure, improved knowledge is essential regarding the long-term effect of hog manure applications on salinity, acidity, soil density, aggregation, and soil strength. A field research project was initiated in 1998 to determine the effects of repeated application of high rates of injected swine manure (up to 13,000 g ac-1) on soil quality in Southern Saskatchewan. In the fall 2001, measurements were made on different soil physical and chemical quality indicators in two of the sites with contrasting soil types: a heavy clay textured soil in the Dark Brown Soil Zone and a sandy loam to loam textured soil in the Brown Soil Zone. At the site with heavy clay textured soil, the high rates of liquid hog manure increased sodium absorption ratio (SAR), electrical conductivity (EC), and surface penetration resistance (SPR) and decreased soil pH; whereas, there were no significant changes on the quality of the surface soil at the sandy loam to loam textured soil to date other than a decrease in surface crusting index. Studies are in progress to include additional sites and also additional soil quality indicator parameters through a longer term monitoring program.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".