An approach for prediction of strength and post yield behaviour for rock masses of low intact strength
Bibliographic record
Abstract
In the design of open pits and shallow foundations engineers are often faced with materials that can be classified as rock but do not fit the current set of criteria used to assess their field strength (saprolites, regoliths, duricrusts (ironstones and carbonate caps), coralline limestones, etc.). These materials can be thought of as transition materials between rock and soil and typically exhibit low strength, which overshadows the presence of any macro features (such as relic structure) in the control of their field behaviour characteristics. A methodology for the estimation of strength parameters for these rock-soil transition materials is presented with guidance for practical application. A hybrid continuum-discontinuum model is employed to verify the approach. The methodology includes a progressive linearization of the Hoek-Brown strength envelope (a → 1) in the transition zone as well as a progressive improvement of the controlling s and parameters to the intact values (s → 1, and m →mi).
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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) | 0.000 | 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 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".