Statistical and numerical analyses of pressuremeter tests in glacial tills
Bibliographic record
Abstract
This study is performed on pressuremeter tests (PMT) in glacial tills based on comprehensive geotechnical investigation programs for a light rail transit project in the City of Toronto. The main objectives are to establish a correlation between SPT-N values and PMT parameters, and the Menard “α” factors for glacial tills. Currently, there are no such relationships available. So first, the pairs of PMT data and SPT-N values are collected at the same depth and test area. With these paired data, two linear correlation equations are established. Then, the numerical simulation is performed for PMTs in glacial tills by using finite element software, Plaxis 2D. The Mohr-Coulomb material model is used to model the different types of soil. The Menard “α” factor is suggested based on the best match between numerical prediction and field PMT. Ranges of SPT-N, EPMT and PL are also suggested for glacial tills.
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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 | 0.004 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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 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".