Soil curling process and its influencing factors
Bibliographic record
Abstract
Soil curling is a common phenomenon in nature due to the rearrangement of soil particles caused by moisture loss. The occurrence of curling in soils significantly affects soil performance in various disciplines. Despite its importance, most existing studies describe the soil curling process within the context of soil desiccation cracking, where boundary conditions facilitating soil curling are not well controlled, or often use the final stage of the desiccation process to infer the soil curling behaviour. Consequently, the underlying soil curling mechanism, the state of the curled soil, and the influencing factors (i.e., clay type, drying temperature, initial water content, and sand content) are not fully understood. In this study, soil curling tests were conducted to study the above-mentioned issues in different types of soils under well-controlled boundary and environmental conditions. It was found that natural clays consisting of higher portions of smectite underwent both upward curling (concave-up) and downward curling (convex-up), while artificial clay experienced only concave-up curling. Concave-up curling initiated when the samples were almost in the saturated condition, while convex-up curling started when the water content of samples was close to their plastic limits. The influencing factors had a profound effect on the moisture evaporation and thus on the soil curling state and its lift-off height. Finally, a conceptual model isproposed to explain the soil curling mechanism and factors influencing soil curling.
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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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".