Chemical and Mineralogical Mapping of Platinum‐Group Element Ore Samples Using Laser‐Induced Breakdown Spectroscopy and Micro‐X‐Ray Fluorescence
Why this work is in the frame
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Bibliographic record
Abstract
Standard techniques for geochemical and mineralogical characterisation are time‐consuming, they can involve significant sample preparation and they are prone to error. The aim of this work is to show how the emerging fast laser‐induced breakdown spectroscopy (LIBS) technique can be valuable for mineral exploration. For this purpose, the well‐established micro‐X‐ray fluorescence (µ‐XRF) technique was used to validate the LIBS data. Two ore samples from the platinum‐group elements (PGE) Lac des Îles mine (Ontario, Canada) were analysed both by LIBS and µ‐XRF. The fast mineralogical and elemental mapping provided by LIBS allowed the identification of four major silicate phases (chlorite, bytownite, actinolite, hornblende) and four minor sulfide phases (Pd‐bearing pentlandite, chalcopyrite, pyrrhotite, pyrite). Multi‐element chemical mapping and mineral characterisation using µ‐XRF corroborated the LIBS analyses for the composition, distribution and abundance of minerals in PGE ore samples. These findings demonstrate the ability of the LIBS technique to perform direct fast high‐resolution mapping of the chemical and mineralogical composition of PGE ore samples. This work highlights the advantages of LIBS for this application of being much faster and more sensitive to trace elements (e.g., Pd), as well as to low atomic number elements.
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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 | 0.001 | 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 | 0.001 |
| 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 it