Modern processing techniques for copper-nickel sulphide concentrates: A review
Bibliographic record
Abstract
Conventional processing of copper-nickel ores involves concentration and flotation resulting in the production of copper-nickel sulphide concentrate, which is then subjected to hydro- or pyrometallurgical processes. At the same time, hydrometallurgical processes failed to find a wide application. This paper considers various pyrometallurgical processes employed by producers in Canada, USA, Australia, China, South Africa and Russia. The authors analyse the processes of electric smelting of raw, briquetted and roasted concentrates with further electric smelting of the resultant products versus autogenous smelting of concentrates. A variety of autogenous processes are examined. According to the authors’ observations, the most advanced process for coppernickel concentrates at the moment includes smelting in a dual-zone Vanyukov furnace, which produces a high-grade matte with the iron concentration of 6–8%, a low-grade waste slag and a single stream of high-sulphur gas. The matte then goes to the hydrometallurgical circuit. This technology saves the need for converter processes or moving smelts in ladles and does not produce low-grade sulphur-containing gases.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".