Measurement of soil variability for probabilistic slope stability analysis
Bibliographic record
Abstract
It has been known for some time that the factor of safety is of little physical significance. Attempting to predict future performance of geotechnical structures using the deterministic factor of safety is fraught with uncertainty and risk. Probabilistic analysis of slope stability can allow the quantification of the input parameter uncertainty and temporal forecasting to be more accurately achieved. Accounting for the spatial correlation structure of soil deposits is essential to proper estimation of probabilities of failure. The current study involves three-dimensional cluster analysis of Cone Penetration Testing with Pore-Pressure measurements (CPTu). The clustered data are to be used in an assessment of the autocorrelation statistics for lacustrine clay foundation soils of a water retention dyke. Dyke 17W is located at the McArthur Falls hydro-electric generating station owned and operated by Manitoba Hydro, located near Winnipeg, Manitoba, Canada. The results of the geostatistical analysis will be modeled as a random field in a probabilistic Monte-Carlo simulation.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".