Spatial association between platinum minerals and magmatic sulfides imaged with the Maia Mapper and implications for the origin of the chromite-sulfide-PGE association
Bibliographic record
Abstract
ABSTRACT The spatial association between Pt minerals, magmatic sulfides, and chromite has been investigated using microbeam X-ray fluorescence (XRF) element mapping and the Maia Mapper. This lab-based instrument combines the Maia parallel energy dispersive (ESD) detector array technology with a focused X-ray beam generated from a liquid metal source. It proves to be a powerful technique for imaging Pt distribution at low-ppm levels on minimally prepared cut rock surfaces over areas of tens to hundreds of square centimeters, an ideal scale for investigating these relationships. Images of a selection of samples from the Bushveld Complex and from the Norilsk-Talnakh ore deposits (Siberia) show strikingly close association of Pt hotspots, equated with the presence of Pt-rich mineral grains, with magmatic sulfide blebs in all cases, except for a taxitic low-S ore sample from Norilsk. In all of the Bushveld samples, at least 75% of Pt hotspots (by number) occur at or within a few hundred microns of the outer edges of sulfide blebs. In samples from the leader seams of the UG2 chromitite, sulfides and platinum hotspots are also very closely associated with the chromite seams and are almost completely absent from the intervening pyroxenite. In the Merensky Reef, the area ratio of Pt hotspots to sulfides is markedly higher in the chromite stringers than in the silicate-dominated lithologies over a few centimeters either side. We take these observations as confirmation that sulfide liquid is indeed the prime collector for Pt and, by inference, for the other platinum group elements (PGEs) in all these settings. We further propose a mechanism for the sulfide-PGE-chromite association in terms of in situ heterogeneous nucleation of all these phases coupled with transient sulfide saturation during chromite growth and subsequent sulfide loss by partial re-dissolution. In the case of the amygdular Norilsk taxite, the textural relationship and high PGE/S ratio is explained by extensive loss of S to an escaping aqueous vapor phase.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".