Selection and operation of Metso Outotec second generation paste thickener at the New Afton Mine
Bibliographic record
Abstract
The New Afton Mine has been in commercial operation since 2012 with the New Afton Tailings Storage Facility (NATSF) used as the primary tailings deposition site. In order to process future underground B3 and C-Zone ores and extend the lifespan of the current operation to 2030, new thickened and amended tailings (TAT) facilities were installed. For the TAT facility, a high yield stress and solids concentration material was required for the mill tailings stream to facilitate amendment with cement and deposition to the Historic Afton open pit (APTSF). A 45 m diameter Metso Outotec second generation paste thickener was selected to achieve the target slurry characteristics and was commissioned in early 2022. This paper discusses the drivers behind the selection of the TAT process for in-pit tailings deposition as well as the selection of the paste thickener. Early operating results and the process optimisation required to achieve the desired overflow and underflow targets are reviewed. Early operating performance is compared to the original design test work. Furthermore, the paper details the value of Metso Outotec second generation paste thickener technology in achieving operational targets for tailings deposition at the New Afton Mine.
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 | 0.001 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".