AN INVESTIGATION ON THE SURFACE CHEMISTRY OF SOME RARE EARTH MINERALS DURING FLOTATION BY TOF-SIMS
Bibliographic record
Abstract
The Thor lake deposit is a world class resource of rare earth (REE) metals and minerals in Canada. Development work to optimize a REE mineral recovery process flow sheet is underway, however, given the ore mineralogy; the developed reagent scheme is relatively complex. As part of a research project, micro flotation tests were conducted on a feed sample in order to examine factors affecting stream partitioning. SEM-EDX was performed to evaluate variability in grain composition between streams (concentrate and tails) and TOF-SIMS surface analysis was used to determine statistically significant differences in surface species particularly related to potential activation (or depression) of the examined mineral phases. SEM-EDX analysis reveal that the concentrate has a significantly higher proportion of REE bearing grains (carbonates and phosphates) relative to the tail (almost none were identified). Spectral fingerprinting by TOF-SIMS has
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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 | 0.001 | 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) | 0.002 | 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".