Development of alternate process flowsheets to recover an unconventional resource rare earth bearing placer garnet and sillimanite from Southeast Coast of India
Bibliographic record
Abstract
In the present study unconventional resources bearing rare earth mineral garnet and sillimanite have been attempted to recover using different alternate flowsheets. The best commercial grade garnet and sillimanite products are obtained from total heavy mineral concentrate recovered by using a spiral concentrator. The garnet product obtained after cleaning with spiral followed by a magnetic separator has a garnet grade of 98.8%, with a recovery of 97.2% and 4.13% overall yield from the bulk sample containing 4.5% garnet. In case of sillimanite also the spiral material is cleaned with a magnetic separator and followed by flotation yields a sillimanite material containing 98.6% sillimanite grade, with a recovery of 95.3% and an overall yield of 3.9% from most feed sample contain 4.0% sillimanite. Therefore, it is recommended to use gravity to remove the gangue ore before it enters the concentrator and to use magnetic equipment for garnet and flotation to obtain commercial grade sillimanite. Rare earth elements can be recovered from this level of garnet and sillimanite.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".