Permeability of mine tailings measured in triaxial cell
Bibliographic record
Abstract
The execution of permeability tests using a triaxial cell makes it possible to eliminate the uncertainties that characterize tests performed using conventional equipment. This paper contains the results of 48 tests carried out on three materials recovered from tailings of Riotinto mines (Spain). The equipment involved a modified triaxial system to facilitate the execution of permeability tests under constant head. The tests were performed on samples consolidated to 50, 100, 200, and 300 kPa for four different hydraulic gradients established by applying a backpressure difference (ΔBp). The magnitude of the backpressure difference was applied as a percentage of the initial effective consolidation pressure, expressed as ΔBp/[Formula: see text]; namely, values of 10%, 15%, 20%, and 25%, which resulted in hydraulic gradients between 5 and 80. The backpressure (Bp) was constant (400 kPa) in all cases, allowing a degree of saturation close to 100% to be achieved. This was verified by calculating Skempton’s B parameter, which was very close to unity in all cases. The results indicate that it is feasible to define an empirical function including the coefficient of permeability (k) and the effective consolidation pressure ([Formula: see text]), the mean effective confining pressure ([Formula: see text]), and the backpressure differential (ΔBp).
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| 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".