Critical insights in laboratory shear wave velocity correlations of clays
Bibliographic record
Abstract
Shear wave velocity, Vs, is an important mechanical–dynamic parameter allowing the characterization of a soil in the elastic range (γ < 10–3%). Thirty-five existing Gmax or Vs laboratory correlations were examined in this study and are grouped into different general forms based on their geotechnical properties. A database of 11 eastern Canadian clay deposits was selected and used for the critical insights. The effect of the coefficient of earth pressure at rest, K0, was also examined. A range of variation for each general form of correlation was determined to take the plasticity index and void ratio values of investigated sites into account. The analysis shows a significant scatter in Vs1 values predicted by existing correlations and raises questions on the applicability of these correlations, especially for eastern Canadian clays. New correlations are proposed for Champlain clays based on laboratory measurement of Vs using the piezoelectric ring-actuator technique, P-RAT, incorporated in consolidation cells. An analysis of P-RAT results reveals the sample disturbance effect and suggests an approach to correct the effect of disturbance on laboratory Vs measurements. The applicability of the proposed correlations, including the disturbance correction, is validated by comparison with in situ measurements using multi-modal analysis of surface waves (MMASW).
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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 | 0.002 | 0.007 |
| 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 | 0.001 |
| 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".