Laboratory study of low-sulfide tailings covers with elevated water table to prevent acid mine drainage
Bibliographic record
Abstract
The use of monolayer covers combined with an elevated water table (EWT) is a promising reclamation method that relies on the low gas-diffusivity of water to limit oxygen ingress into potentially acid-generating tailings. A monolayer cover is installed over the sulfidic material and the water table level is controlled to maintain the tailings close to saturation. A protocol including laboratory columns was conducted to evaluate the sensitivity of the technique to parameters including cover thickness, water table level, and the presence of an anti-evaporation layer. Two types of desulfurized tailings were evaluated: silty tailings from Westwood mine and sandy tailings from Goldex mine. Data used to evaluate the covers performances included volumetric water content, suction, oxygen concentrations, and oxygen consumption. Results showed that both cover materials could be used to maintain the reactive tailings at a degree of saturation ≥90% when the EWT level was maintained at a maximum distance of 1 m below the tailings surface. The finer Westwood material showed a better capacity for limiting oxygen migration through the cover, with a maximum flux of 5.7 mol·m−2·year−1 measured near the cover base.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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 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".