Distributed soil displacement and pressure associated with surface loading
Bibliographic record
Abstract
Soil compaction is an inevitable result of agricultural practices.It alters physical properties of soil and tends to be undesirable as it adversely affects water and nutrient penetration.Furthermore, additional energy is spent to till the soil.Although a tremendous amount of research has been conducted in the area of soil compaction, the focus has been primarily on surface soil displacement.Realizing that the observed soil displacement is the cumulative effect from the compaction of subsurface layers, this research discusses the displacement and distributed pressure through the soil from a surface load.A given volume of soil of known density and moisture content was loaded at the surface with a slowly applied force using an Instron ® testing machine.The distribution of the pressure and displacement profile from the surface to depth was measured to provide insight into the formation of the subsurface soil structures.The nonlinear exponential decay of the soil displacement (compaction) from the surface to a given depth converges to zero at the location of a hard, compact layer or a point where no soil movement occurs, regardless of the initial soil compaction.By increasing soil moisture content and decreasing soil bulk density, the vertical soil displacement increased at the surface and within the soil profile, and the pressure distribution decreased with depth.Changing the shape of loading surface had minimal effect on soil displacement.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".