Supergene mobilization and redistribution of platinum-group elements in the Merensky Reef, eastern Bushveld Complex, South Africa
Bibliographic record
Abstract
ABSTRACT Near-surface supergene ores of the Merensky Reef in the Bushveld Complex, South Africa, contain economic grades of platinum-group elements, however, these are currently uneconomic due to low recovery rates. This is the first study that investigates the variation in platinum-group elements in pristine and supergene samples of the Merensky Reef from five drill cores from the eastern Bushveld. The samples from the Richmond and Twickenham farms show different degrees of weathering. The whole-rock platinum-group element distribution was studied by inductively coupled plasma-mass spectrometry and the platinum-group minerals were investigated by reflected-light microscopy, scanning electron microscopy, and electron microprobe analysis. In pristine (“fresh”) Merensky Reef samples, platinum-group elements occur mainly as discrete platinum-group minerals, such as platinum-group element-sulfides (cooperite–braggite) and laurite as well as subordinate platinum-group element-bismuthotellurides and platinum-group element-arsenides, and also in solid solution in sulfides (especially Pd in pentlandite). During weathering, Pd and S were removed, resulting in a platinum-group mineral mineralogy in the supergene Merensky Reef that mainly consists of relict platinum-group minerals, Pt-Fe alloys, and Pt-oxides/hydroxides. Additional proportions of platinum-group elements are hosted by Fe-hydroxides and secondary hydrosilicates (e.g., serpentine group minerals and chlorite). In supergene ores, only low recovery rates (ca. 40%) are achieved due to the polymodal and complex platinum-group element distribution. To achieve higher recovery rates for the platinum-group elements, hydrometallurgical or pyrometallurgical processing of the bulk ore would be required, which is not economically viable with existing technology.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".