Mechanical response of highly gap-graded mixtures of waste rock and tailings. Part II: Undrained cyclic and post-cyclic shear response
Bibliographic record
Abstract
Mixing of waste rock and tailings as a homogeneous mixture (referred to as “paste rock”) has been suggested as a favourable approach to overcome deficiencies associated with traditional methods of mine waste disposal. In consideration of the current limited understanding of the fundamental mechanical response of paste rock, a laboratory research program was undertaken to investigate the monotonic and cyclic shear response of paste rock. This paper presents the findings from undrained cyclic triaxial shear testing conducted on saturated paste rock specimens reconstituted such that the tailings would “just fill” the void spaces between the coarse particles of the skeleton. During undrained cyclic loading, paste rock typically exhibited a cumulative decrease in effective stress along with a progressive degradation of shear stiffness. The material generally displayed a higher tendency for strain development under cyclic loading when compared with rock-only and tailings-only specimens subjected to similar consolidation and cyclic loading conditions. However, no strain-softening or loss of shear strength was observed, suggesting that the material is unlikely to experience flow failure under undrained cyclic loading. The cyclic shear resistance was relatively insensitive to the initial effective confining pressure ([Formula: see text]) for the tested stress levels of [Formula: see text] < 400 kPa.
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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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".