Structural and geochemical ore-forming processes in deformed gold deposits: towards a multiscale and multimethod approach
Bibliographic record
Abstract
Abstract Integrating structural control on mineralization and geochemical ore-forming processes is crucial when studying deformed ore deposits. Yet structural and geochemical data are rarely acquired at the same scale: structural control on mineralization is typically investigated from the district to the deposit and macroscopic scales whereas geochemical ore processes are described at the microscopic scale. The deciphering of a deformation–mineralization history valid at every scale thus remains challenging. This study proposes a multiscale approach that enables the reconciliation of structural and geochemical information collected at every scale, applied to the example of the Galat Sufar South gold deposit, Nubian shield, NE Sudan. It gathers field and laboratory information by coupling a classical petrological–structural study with high-resolution X-ray computed tomography, electron back-scattered diffraction and laser ablation inductively coupled plasma mass spectrometry on mineralized sulfide mineral assemblages. This approach demonstrates that there is a linear control on mineralization expressed from the district to microscopic scales at the Galat Sufar South gold deposit. We highlight the relationships between Atmur–Delgo suturing tectonics, microdeformation of sulfide minerals, syn-pyrite recrystallization metal remobilization, gold liberation and ore upgrading. Our contribution therefore represents another step forward in a holistic field-to-laboratory approach for the study of any other sulfide-bearing, structurally controlled ore deposit type.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".