Influence of Tectonic Factor on Porphyry Copper Deposits Localization and Distribution (Arasbaran District, NW Iran): Synthesis of Alteration Patterns and Lineaments Using Digital Techniques
Bibliographic record
Abstract
The Kighal and Bormolk porphyry copper deposits (PCDs) are known subeconomic deposits and are ~10 km south of Sungun, the world-class copper mine in NW Iran. The deposits are located in the Azerbaijan plateau, within Alborz, Zagros, and Caucasus Mountain ranges, having undergone active tectonics, including uplift and thrust-folding from the Cimmerrian Orogeny. The sub-economic nature of the Kighal and Bormolk deposits, despite their relatively close distance and age and lithologic similarity to those of the Sungun deposit, has been discussed. The Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) and Landsat 8 Operational Land Imager (OLI) imagery were used to map alteration patterns and lineaments associated with these deposits. In order to discriminate alteration minerals of the deposits in comparison with those in the Sungun deposit, the ASTER image was processed using False Color Composite (FCC), Band Ratio (BR), Principal Component Analysis (PCA), Minimum Noise Fraction (MNF), and Mixture-Tuned Matched-Filtering (MTMF) techniques, which recognize seven alteration types in the Kighal‒Bormolk area and three types in the Sungun area, including its more intense alteration systems. The results were verified by field observations, mineralogical, and X-ray diffraction (XRD) studies. Also, lineament extraction of DEM and Landsat 8 OLI data by Envi 5.1, Geomatica, ArcGIS 10.6, and Rockworks 16, displayed a lower density of fault intersections in the Kighal‒Bormolk area. Additionally, NW‒SE trending lineaments of the Sungun deposit, which is in accordance with most of the valuable porphyry copper deposits in Iran, are taken into account.
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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 | 0.002 | 0.002 |
| 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) | 0.001 | 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".