Microstructural control on the trace element distribution and Au concentration in pyrite nodules
Why this work is in the frame
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Bibliographic record
Abstract
The crystal growth history of an Au-rich sedimentary pyrite nodule from the Timmins-Porcupine Au camp, Ontario, Canada, has been investigated using Electron Backscattered Diffraction and Laser Ablation Inductively Coupled Plasma Mass Spectrometry techniques to study the crystallographic processes controlling metal deportment in the pyrite structure. Results show four distinct growth stages characterized by different pyrite microstructures, crystal forms and trace element compositions. A direct link is observed between the growth of octahedral facets in pyrite and the development of primary (non-tectonic) subgrain boundaries. Furthermore, zones with a high abundance of subgrain boundaries have the highest Au, As, Ag and Cu (and other metals) contents – suggesting metal distribution is linked to the development of microstructures. Finer-grained aggregates are characterized by higher grain boundary density than in coarse areas, making higher trace element concentrations inversely proportional to grain size. Our results indicate that the high Au concentrations (~100 ppm) in pyrite represent a primary feature related to nodule growth, instead of secondary enrichment processes, and highlight the possibility that sediment-hosted pyrite nodules could represent a metal-rich geochemical reservoir for the formation of younger orogenic Au deposits. • Microstructures in diagenetic pyrite nodules are linked to metal incorporation. • Au, As, Ag, and Cu are concentrated in non-tectonic grain and subgrain boundaries. • Grain and subgrain boundaries are interpreted as primary growth structures. • The incorporation of Au, As, Ag, is a primary feature in diagenetic pyrite nodules. • High S content during diagenesis is related with higher Au incorporation.
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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) | 0.000 | 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 it