Rare Earth Elements (La, Ce, Pr, Nd, and Sm) from a Carbonatite Deposit: Mineralogical Characterization and Geochemical Behavior
Bibliographic record
Abstract
Geochemical characterization including mineralogical measurements and kinetic testing was completed on samples from the Montviel carbonatite deposit, located in Quebec (Canada). Three main lithological units representing both waste and ore grades were sampled from drill core. A rare earth element (REE) concentrate was produced through a combination of gravity and magnetic separation. All samples were characterized using different mineralogical techniques (i.e., quantitative evaluation of minerals by scanning electron microscopy (QEMSCAN), X-ray diffraction (XRD), and scanning electron microscopy with X-ray microanalysis (SEM-EDS)) in order to quantify modal mineralogy, liberation, REE deportment and composition of REE-bearing phases. The REE concentrate was then submitted for kinetic testing (weathering cell) in order to investigate the REE leaching potential. The mineralogical results indicate that: (i) the main REE-bearing minerals in all samples are burbankite, kukharenkoite-Ce, monazite, and apatite; (ii) the samples are dominated by REE-free carbonates (i.e., calcite, ankerite, and siderite); and (iii) LREE is more abundant than HREE. Grades of REE minerals, sulfides and oxides are richer in the concentrate than in the host lithologies. The geochemical test results show that low concentrations of light REE are leached under kinetic testing conditions (8.8–139.6 µg/L total light REE). These results are explained by a low reactivity of the REE-bearing carbonates in the kinetic testing conditions, low amounts of REE in solids, and by precipitation of secondary REE minerals.
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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 | 0.001 |
| 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) | 0.001 | 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".