Exploration for Platinum-Group Minerals in Till: A New Approach to the Recovery, Counting, Mineral Identification and Chemical Characterization
Bibliographic record
Abstract
The discovery of new mineral deposits contributes to the sustainable mineral industrial development, which is essential to satisfy global resource demands. The exploration for new mineral resources is challenging in Canada since its vast lands are mostly covered by a thick layer of Quaternary sediments that obscure bedrock geology. In the course of the recent decades, indicator minerals recovered from till heavy mineral concentrates have been effectively used to prospect for a broad range of mineral deposits including diamond, gold, and base metals. However, these methods traditionally focus on (visual) investigation of the 0.25–2.0 mm grain-size fraction of unconsolidated sediments, whilst our observations emphasize on higher abundance, or sometimes unique occurrence of precious metal (Au, Ag, and platinum-group elements) minerals in the finer-grained fractions (<0.25 mm). This study aims to present the advantages of applying a mineral detection routine initially developed for gold grains counting and characterization, to platinum-group minerals in <50 µm till heavy mineral concentrates. This technique, which uses an automated scanning electron microscopy (SEM) equipped with an energy dispersive spectrometer, can provide quantitative mineralogical and semi-quantitative chemical data of heavy minerals of interest, simultaneously. This work presents the mineralogical and chemical characteristics, the grain size distribution, and the surface textures of 2664 discrete platinum-group mineral grains recovered from the processing of 5194 glacial sediment samples collected from different zones in the Canadian Shield (mostly Quebec and Ontario provinces). Fifty-eight different platinum-group mineral species have been identified to date, among which sperrylite (PtAs2) is by far the most abundant (n = 1488; 55.86%). Textural and mineral-chemical data suggest that detrital platinum-group minerals in the studied samples have been derived, at least in part, from Au-rich ore systems.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".