Bibliographic record
Abstract
The spiral concentrator is a mineral processing device that separates mineral particles according to their densities and to a lesser extent particle size. In this thesis, a four-turn WALKABOUT PW1 spiral concentrator was used to investigate the particle movement inside the trough of spiral concentrator. For the experiments, a synthetic ore was prepared to mimic a real iron ore from Mont-Wright (Quebec). The sample consisted of 40% magnetite (ρ = 5.17 g/cm3) and 60% quartz (ρ = 2.65 g/cm3) with a size range smaller than 850 µm. In order to produce a comprehensive data set of particle distribution across the trough in every turn of spiral concentrator, the material was sampled at the end of every turn. The separation of mineral particles observed was as described in the literature, with small and dense particles tending towards the centre of the spiral, on the other hand, large light particles tending towards the outside of the spiral; and a small portion of the large heavy particles would report to the outside. The flow rate and physical properties of the slurry were analyzed from the sampled materials. A database produced from the experiment was used to build partition curves of the magnetite and quartz for every turn of the spiral. A partition curve model was applied to predict the recovery of magnetite in the virtual fifth turn of the spiral. The understanding of the separation mechanism gained in this study will be of interest to improve the design of spiral concentrator and to adjust the operational parameters of mineral concentration.
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 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 | 0.000 | 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) | 0.000 | 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".