Equations for the entire soil-water characteristic curve of a volume change soil
Bibliographic record
Abstract
Numerous curve-fitting equations have been proposed for soil-water characteristic curves. While these equations have been of considerable value in geotechnical and geoenvironmental engineering, the equations are not able to adequately fit gravimetric soil-water characteristic curve data over the entire range of soil suction for a soil that changes volume when suction is changed. Two new equations for the soil-water characteristic curve are presented in this paper. One equation has curve-fitting parameters that bear a meaningful relationship to conventional physical soil properties (e.g., air-entry value and residual soil suction), but the equation is somewhat complex. The equation is particularly useful for sensitivity type studies when undertaking computer modeling. The other equation is relatively simple to use and is developed as a conventional curve-fitting equation. The two equations are used to best-fit several soil datasets. Both equations perform well and can be used in research and engineering practice to define the gravimetric water content versus soil suction relationship for a soil exhibiting volume change.
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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 | 0.000 |
| 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 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".