Ferralsol Porosity and Density After Mechanical Scarification and Crop Rotation Systems
Bibliographic record
Abstract
With intensive cultivation and the lack of crop rotation, the no-tillage system has been showing compacted areas. For its reduction, mechanical scarification and crop rotation has been recommended. Thus, the present study aimed to evaluate in a no-tillage system the effect of mechanical scarification and crop rotation systems on soil porosity and density after 18 months. The experimental design used was randomized blocks in a split-plot scheme, with four replications. The main plots consisted of maintaining the no-tillage system and minimal soil preparation with a chisel, carried out before the cultivation of cover plants. The subplots were composed of different plant species grown in winter: wheat, consortium of forage pea + black oat and consortium of black oat + forage turnip. Both were succeeded by cultivation of soy and lupin. Macroporosity, microporosity, total porosity and bulk density were evaluated. After 18 months, the scarified soil showed a higher bulk density (0.10-0.15 m layer) when compared to the no-tillage system, demonstrating that this isolated decompression alternative does not improve the physical properties of the soil. The area in succession to oat + turnip/soybean/lupin showed lower bulk density.
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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 | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".