Numerical Prediction of Expansive Soil Behavior in Changing Climate
Bibliographic record
Abstract
The prediction of expansive soil shrinkage/swelling response to climate cycles is of great importance for geotechnical engineers. The climate change is anticipated to cause significant changes in the hydrological cycles that consequently results in higher risk of damage to the structures constructed on expansive soils. \nIn this study, a single stress state variable framework was adopted to describe the void ratio as a function of effective stress for soils in unsaturated state. A two-dimensional finite element model that couples variably saturated flow and stress-strain analysis was developed to simulate the behavior of expansive clay subject to change in soil moisture content. \nThe developed numerical model was used to assess the impact of climate change on the behaviour of Regina Clay in the city of Regina, Saskatchewan. The results indicated that the frequency of large expansive ground heaving events is considerably higher under critical future Regina climate scenario compared to historical climate.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".