Effect of climate change on earthen embankments in Southern Ontario, Canada
Bibliographic record
Abstract
Soil embankments are an integral part of transportation networks and are vulnerable to climate change due to their continuous exposure to the environment. The direct and indirect costs associated with an embankment failure can be significant and it is critical to ensure against the adverse effects of a changing climate. This research aims to quantify the probable stability effects of regular and extreme climate change on a highway embankment in Southern Ontario, Canada. The impact of climate change was quantified for two different embankment fills (sand and silt) by comparing the stability results of historical climate with a 90-year future climate data set. This analysis was accomplished by coupling changes in pore-water pressures (using a two-dimensional (2D) transient unsaturated seepage finite-element model) with a 2D limit equilibrium unsaturated slope stability model. The results indicate that future climate could increase the cumulative annual net infiltration by as much as 41%, which would decrease the embankments’ factor of safety by as much as 30%. It was also found that hydraulic properties play a critical role in embankment stability for different climate scenarios and suitable fill material based on the geographic region should be selected to ensure the safety of the embankments against climate change.
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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 | 0.002 | 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".