Geotechnical Parameters of Landslide-Prone Laflamme Sea Deposits, Canada: Uncertainties and Correlations
Bibliographic record
Abstract
Due to inherent variability arising from unpredictable geological depositional and post-depositional processes, the geotechnical parameters of Laflamme sea clay deposits remain highly uncertain. This study aims to develop and apply a methodology to assess the uncertainties of geotechnical parameters using statistical distributions for a landslide-prone Saguenay Lac-Saint-Jean (SLSJ) region. We used the measured physical and mechanical parameters of Laflamme Sea clays of various locations in the SLSJ region to characterize the geotechnical parameters in a representative manner. Goodness-of-fit tests assign each physical and mechanical parameter a distribution function for their descriptive analysis. We found that the quality of these tests is significantly influenced by outliers. The detected outliers in the dataset considerably impact the distribution type and the uncertainties of the specific geotechnical parameter. Subsequently, appropriate distribution functions for each parameter were assigned after treating the outliers. The derived coefficient of variability values for the SLSJ region were significantly high in comparison to the literature with cone penetration test data being only the exception. Finally, the results indicated that the uncertainties of geotechnical parameters of the Saguenay-Lac-Saint-Jean region marine clays are high as compared to Scandinavian clays and are relatively comparable to other eastern Canadian clays.
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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) | 0.001 | 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".