Bibliographic record
Abstract
The process using lignosulfonates for acidic rock drainage (ARD) treatment is referred to as the Lignor process. Lignosulfonates are waste by-products produced in the sulfite pulping process. The present study has shown lignosulfonates are able to protect lime from developing an external surface coating, and hence to favor its dissociation. Further, the addition of lignosulfonates to ARD solutions increased the dotting and settling rate of the formed sludge. The capability of lignosulfonates to form stable metal-lignin complexes makes them very useful in retaining metal ions and thus improving the long-term stability of the sludge against leaching. The Lignor process involves metal sorption with lignosulfonates, ARD neutralization by lime to about pH 7, pH adjustment with caustic soda to 9.4 - 9.6, air oxidation to lower the pH to a desired level, and addition of a minimum amount of FeCl3 for further removal of dissolved metals. The Lignor process removes all concerned metals (especially Al and Mn) from the ARD of the Britannia Mine (located at Britannia Beach, British Columbia, Canada) to a level lower than the limits of the B.C. Regulations. Compared with the high-density sludge (HDS) process, the Lignor process has many advantages, such as considerable savings in lime consumption, greatly reduced sludge volume, and improved sludge stability.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".