Assessment of tillage effects on soil quality of pastures in South Africa with indexing methods
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Soil quality of pastures changes through time because of management practices. Excessive soil disturbance usually leads to the decline in soil quality, and this has resulted in concerns about kikuyu (Pennisetum clandestinum)–ryegrass (Lolium spp.) pasture systems in the southern Cape region of South Africa. This study aimed to understand the effects of tillage on soil quality. The soil management assessment framework (SMAF) and the locally developed soil quality index for pastures (SQIP) were used to assess five tillage systems and were evaluated at a scale inclusive of variation in topography, pedogenic characteristics and local anthropogenic influences. Along with assessment of overall soil quality, the quality of the physical, chemical and biological components of soil were considered individually. Soil physical quality was largely a function of inherent pedogenic characteristics but tillage affected physical quality adversely. Elevated levels of certain nutrients may be warning signs to soil chemical degradation; however, tillage practice did not affect soil chemical quality. Soil disturbance and the use of herbicides to establish annual pastures has lowered soil biological quality. The SQIP was a more suitable tool than SMAF for assessing soil quality of high-input, dairy-pasture systems. SQIP could facilitate adaptive management by land managers, environmentalists, extension officers and policy makers to assess soil quality and enhance understanding of processes affecting soil quality.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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 it