Bibliographic record
Abstract
Birchtree is an ultramafic ore body and prior to 2003, represented one third of the production for Inco's Thompson operation. The ultramafic host rocks are high in MgO which, when processed through the smelter, promotes problems in the roasters and converters due to the high liquidus temperature. In October 2003, production from Birchtree mine ramped up to more than half of the total feed to the mill. The mill cannot produce a suitable concentrate for the smelter with current circuit configuration and operating practices. The target for the mill was to produce a nickel concentrate with less than 3% MgO. Continuous mini flotation cells were used to explore processing options. Two campaigns were carried out. The first looked at rejecting the magnesium silicate minerals with the use of reagents from the rougher and scavenger concentrates. Reagents included sodium silicate, guar gum and two types of CMC. Results indicated that current plant practice of CMC addition to the scavenger circuit favours minimizing MgO grade in concentrate. The second campaign focused on rejecting MgO minerals from the rougher-cleaner concentrate with the use of a dilute CMC solution. Flotation retention time, CMC dosage rate, and conditioning time, were varied. Results indicate that 0.1 g CMC per kilogram of solid in slurry produced a concentrate grading <3.0% MgO.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".