AN OVERVIEW OF CHALCOPHILE ELEMENT CONTENTS OF PYRRHOTITE, PENTLANDITE, CHALCOPYRITE AND PYRITE FROM MAGMATIC NI-CU- PGE DEPOSITS
Why this work is in the frame
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Bibliographic record
Abstract
We have compiled the trace element concentrations in pyrrhotite, pentlandite, chalcopyrite, and pyrite from magmatic Ni-Cu-PGE ore deposits with the aim of understanding their petrogenesis and whether these minerals can be used as indicator minerals. Among the samples, there are some of the most studied world-class Ni-Cu- (Aguablanca, Duluth, Jinchuan, Noril’sk-Talnakh-Kharaelakh, Sudbury, Voisey’s Bay, and others) and PGE-dominated (Bushveld, Lac des Iles, Stillwater, Great Dyke, and Penikat) deposits. Crustal assimilation may be constrained using As/Se and Sb/Se ratios in pentlandite. The degree of interaction between the silicate and sulfide liquids (R-factor) can be estimated by the content of highly chalcophile elements (Dsulf liq/sil liq above 1000) in sulfide minerals. The fractional crystallization of the sulfide liquid can be traced using Se/Te ratios of pentlandite. Pyrite formed by exsolution from MSS has higher Rh, Ru, Ir, and Os than co-existing pyrrhotite, whereas pyrite formed by hydrothermal alteration of pyrrhotite inherits the Rh, Ru, Ir, and Os contents of the pyrrhotite it replaced. Sulfide minerals are preserved in transported glacial cover and their trace element chemistry can be used to discriminate their source. Pentlandite from Ni-Cu deposits has much lower Rh and Pd concentrations than those from PGE-dominated deposits, pyrite from magmatic deposits has higher Co/Sb and Se/As ratios relative to pyrite from hydrothermal deposits, and chalcopyrite from magmatic deposits has much higher Ni and lower Cd concentrations than those from hydrothermal deposits.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it