Effect of saturation procedures on direct simple shear testing of silt tailings
Bibliographic record
Abstract
The direct simple shear (DSS) test carried out under constant volume (CV) conditions forms one of the primary laboratory techniques to characterise soils and tailings. The use of CV conditions to simulate undrained shearing is supported by historical evidence on the testing of a saturated clay and sands, with this evidence being incorporated into current guidelines and state of practice procedures. However, some recent comparisons of the results of undrained hollow cylinder simple shear (HCSS) and CV DSS tests on predominately silt gold tailings adopting state of practice test procedures (i.e. inundation of the sample after loose moist tamping) showed much less post-peak strength loss in the gold tailings than the undrained HCSS tests. The current study investigated this discrepancy further by carrying out DSS tests under high back pressures, undrained simple shear tests with flexible membrane and constant cell pressure and DSS tests after flushing with carbon dioxide and with use of a small back pressure. In all cases, the undrained tests or DSS tests with greater effort put towards saturation exhibited greater post-peak strength loss more consistent with the HCSS and the critical state line. The importance of these results on the estimation of tailings brittleness in engineering practice was outlined.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".