Slope Failure in Cretaceous Clay Shale in Western Manitoba: A Case Study
Bibliographic record
Abstract
Slope instabilities have been affecting the grade slope of Provincial Trunk Highway 5 near the junction with Provincial Trunk Highway 10 in northwestern Manitoba for over 50 years. In recent years, the instabilities have resulted in significant damage to the highway pavement surface. In 2011, Manitoba Infrastructure and Transportation initiated a geotechnical investigation to gain a better understanding of the failure, identify possible failure mechanisms, and explore various remedial design alternatives in order to stabilize the slope. The site was instrumented with slope inclinometers and vibrating wire piezometers, and monitored over a period of two years. An extensive laboratory testing program was completed to compare the results of direct shear tests and torsional ring shear tests for determining the shear strength of the underlying Cretaceous clay shale. Measured values were compared with values back analyzed using limit equilibrium analysis. A coupled finite element model was used to model the expected excess porewater pressure response, and therefore the stability of the slope, during construction of a stabilization berm. It was subsequently calibrated to agree with the measured porewater pressure responses from the instrumentation. Finally, spring flood conditions were simulated to determine the effect of multiple flash flood events on the stability of the slope.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".