Effectiveness of Covers and Liners Made of Red Mud Bauxite and/or Cement Kiln Dust for Limiting Acid Mine Drainage
Bibliographic record
Abstract
This paper presents a laboratory investigation to evaluate the capacity of alkaline residues to inhibit acid mine drainage. Column tests were used to evaluate the geochemical behavior of cement kiln dust (CKD) and red mud bauxite (RMB) used as covers, liners, or mixed with acid producing tailings and waste rocks. The most important indicators of neutralization are pH and the concentrations of metals in solution. Initial leachate pH of samples with an alkaline cover composed of 10% CKD or 10% of a mixture of CKD and RMB was low, but rapidly increased to near 7.0 and stabilized for the duration of this study. The use of alkaline materials as a liner had a positive effect on the reduction of Fe, SO4 and other metals such as Cu and Zn concentrations and the number of viable bacteria. In the cases where the alkaline layer was used as a liner or mixed with the waste rocks, near neutral pH values were rapidly reached in the leachate. However, in these columns the leachate pH values decreased over time.
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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".