Susceptibility to Compaction, Load Support Capacity, and Soil Compressibility of Hapludox
Bibliographic record
Abstract
Models that integrate the influence of soil intrinsic attributes on the estimation of soil compaction are scarce for Hapludox. The present study tested the hypothesis that the compressive behavior of Hapludox with wide variations in intrinsic soil attributes can be estimated based on pedotransfer functions (PTFs). The general goal of this research was to determine the effect of intrinsic soil attributes on the susceptibility to compaction, preconsolidation pressure and compression curve of Hapludox, and to develop PTFs that allow the estimation of these parameters based on easily measurable soil attributes. The study was conducted on a soil toposequence that includes a sandy Typic Hapludox, a loamy Typic Hapludox, and a clayey Rhodic Hapludox. The uniaxial compression test was applied to 50 undisturbed soil samples at matric potential values of −10 and −100 kPa. After load withdrawal, soil bulk density, void ratio, gravimetric soil water content, particle‐size distribution, particle density, and organic matter were determined. The compression curves, the compression index, and the preconsolidation pressure were obtained. The relationship between the compression index, soil bulk density, and clay content was statistically significant with R2 = 0.77. Organic matter and soil water content did not affect the compression index. The preconsolidation pressure was significantly related with soil bulk density, soil water content, and clay content (R2 = 0.70), but was unaffected by organic matter. Soil compressibility was dependent on soil bulk density. A nonlinear model fitted the data with R2 = 0.90 allowing to predict the compressibility of soils for a wide range of stresses and inherent soil properties.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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".