Extended multivariate approach for uncertainty reduction in the assessment of undrained shear strength in clays
Why this work is in the frame
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Bibliographic record
Abstract
Important features of the multivariate approach are discussed, and an extension to this approach is proposed whereby the total uncertainty in site investigation methods due to spatial averaging is assessed prior to its adoption. Results from a site investigation of spatially averaged values of undrained shear strength ([Formula: see text]) and the corresponding coefficient of variation ([Formula: see text]) in Veda sulphide clay were used as a practical illustration of the extended multivariate approach and provide a basis for discussion. The inherent variability and scales of fluctuation for different methods are presented. The study shows the usefulness of the extended multivariate approach for the evaluation of representative values of [Formula: see text] and [Formula: see text] based on results from different methods. It is also a way of implicitly reducing the transformation errors that arise when a property is derived from measurement results. Nevertheless, considerable care must be taken as a much lower COV for one method will have a significant impact on the results.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it