Chemically induced changes in the geotechnical response of cementing paste backfill in shaking table test
Bibliographic record
Abstract
Cemented paste backfill (CPB) is extensively used for underground mine support and/or tailings management. However, CPB behavior under cyclic loadings might be affected by the chemistry of its pore-water, which often contains sulphate ions. Till today, no studies have addressed the effect of sulphate on the response of CPB to cyclic loadings by using shaking table technique. This study presents new findings of assessing the effect of the sulphate in the pore water of CPB on its geotechnical response to cyclic loading by using shaking table. CPB mixtures were prepared (with and without sulphate), poured into a flexible laminar shear box, cured to 4 h, and then exposed to cyclic loading using one-dimensional (1D) shaking table. Several parameters (e.g. pore water pressure , settlement, lateral deformation , acceleration, electrical conductivity , effective stress, and liquefaction susceptibility) were monitored or determined before, during, and after shaking. Obtained results indicate that the sulphate-bearing CPB cured to 4 h can be prone to liquefaction under the studied conditions. However, sulphate-free CPB samples are resistant to liquefaction. These results are expected to contribute to a better understanding of the effect of water chemistry on the cyclic behavior of CPB, consequently enhancing the cost-effective design of CPB structures.
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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 | 0.000 |
| 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) | 0.002 | 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".