Remote sensing techniques for mapping hydrothermal alteration zones of volcanogenic massive sulfide deposits in Red Sea Hills, NE Sudan
Bibliographic record
Abstract
The area of our research lies in the Red Sea Hills region in NE Sudan and occupies a central position in the Nubian part of the late Proterozoic Nubian-Arabian Shield. The Red Sea Hills have received considerable studies in structural and remote sensing aspects in the past decades. Most of the studies were conducted to understand the structural evolution and the tectonic development of the Nubian-Arabian Shield in northeast Sudan. However, the link between the structural elements and the mineralization in the area is not well established, and in several parts of the region the identification of mineral deposits is also not well known. Therefore, the present study deals mainly with the determination of mineralization zones and highlights the structural elements of the study area. The processing of Landsat 8 OLI images has included different methods such as band rationing, density slicing, and featured oriented principal component analysis. These methods allowed us to identify the zones of hydrothermal alteration, which could be associated with ore mineralization within the study area. These mapped alteration zones were verified with the aid of the obtained field and geochemical data. Interpretation of the detailed geochemical data set of the study area revealed the presence of Au/Cu/Zn anomalies at most of the perspective locations outlined in the hydrothermal composite map, uniquely supporting the usefulness of remote sensing methods. The structural analysis of the brittle deformation manifestations revealed that the NE–SW fracture system represents the main controlling factor on the occurrence of the mineralization in our research area.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| 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 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".