Extraction of Ferronickel Concentrate by Reduction Roasting-Magnetic Separation from Low Grade Laterite Nickel Ore under the Action of Compound Additives
Bibliographic record
Abstract
Nickel is an important strategic metal in the world. As the sulfide ore containing high-grade nickel is increasingly depleted, the laterite nickel ore, which is rich in resources, has attracted people’s attention. In this paper, the reduction roasting-magnetic separation process is used to study the method of preparing ferronickel concentrates from low-grade laterite nickel ore under the action of composite additives (Na2CO3 and CaF2). The research results showed that when the ratio of additives Na2CO3 and CaF2 was 1:7, reduction temperature was 1250°C, reduction time was 60 min, magnetic field strength was 150 mT, and wet grinding time was 12 min, the nickel grade and recovery extent were 8.39 wt.% and 98.54%, iron grade and recovery extent were 67.70 wt.% and 71.73%.
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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 | 0.000 | 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".