SOIL DENSITY AND OPTIMUM MOISTURE FOR SOIL COMPACTION IN FIVE SOIL CLASSES IN WESTERN BAHIA STATE
Bibliographic record
Abstract
The transformation of natural ecosystems into agricultural environments modifies the soil structure and it may result in its compaction. Therefore, the objective of this work was to determine the optimum moisture for soil compaction (wot) and maximum soil compaction density (Dsmax) in different soil classes in western Bahia State. The samples were collected in five sites covering different soil classes: Orthic Quartzarenic Neosol (RQ), Orthic Ebanic Vertisol (VEo), Haplic Cambisol (CX) and two Red-Yellow Latosol, one already cropped (LVA) and another with native forest (LVA1). Wot and Dsmax were determined according to ABNT NBR 7182 (1986) standards. Data were submitted to a regression analysis and also to the analysis of the principal components (PCA). Wot presented a decreasing order: VEo> LVA> LVA1> CX> RQo, ranging between 8.20 and 15.00% and Dsmax showed the following order RQo> LVA> LVA1> CX> VE, ranging between 1.34 and 1,92 Mg.m-3. The wot was directly proportional to the clay content and the organic carbon and inversely proportional to the soil sand content. For Dsmax, the influence of the clay was inversely proportional whereas in wot, this variable promoted the growth.
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How this classification was reachedexpand
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 | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".