An investigation into processing fine magnetite using a magnetic hydrocyclone
Bibliographic record
Abstract
As a consequence of fine grinding in the mineral processing industry, fine material containing quantities of valuable metal is being lost to tailing dams, wastewater and mine drainage. The processing of ultrafine particles has always been a challenge in the mining industry, thus typically, fine components are often considered waste during mineral processing. In addition, magnetic adsorbents are also being investigated as a method of processing wastewater, leading to the need for methods of recovering fine material post adsorption. A method of fines recovery, using a magnetic hydrocyclone to increase ultrafine and fine (−38 µm) material recovery from slurry was investigated in this paper. The attached permanent (Nd-Fe-B) magnet concentrated magnetite particles to the underflow and increased recovery by 15.4%, 5.6% and 2.0% on average for ultrafine (<5 µm) magnetite and two size distributions of fine magnetite (<38 µm), respectively, when compared to a conventional hydrocyclone.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.021 | 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 teacher head, 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".