Alteration Mineralogy of the Zhengguang Epithermal Au-Zn Deposit, Northeast China: Interpretation of Shortwave Infrared Analyses During Mineral Exploration and Assessment
Bibliographic record
Abstract
Abstract Alteration mineralogy from shortwave infrared (SWIR) spectroscopy was compared with X-ray diffraction (XRD) analyses for samples from the Zhengguang intermediate sulfidation epithermal Au-Zn deposit, eastern Central Asian orogenic belt, northeast China. The SWIR and XRD analyses indicate that alteration minerals in the vein-adjacent halo mainly comprise quartz, illite, and locally pyrite (QIP) and chlorite, whereas samples from the pervasive propylitic alteration of host basaltic andesite lava contain epidote, chlorite, carbonate, montmorillonite, and locally illite. SWIR mineral identifications from automated mineral identification software may not always be accurate; thus, the results should be validated by the user. The wavelength position of the Al-OH (~2,200 nm; wAlOH) absorption feature can be used to approximate the composition of illite or white mica. However, caution is required when using the wAlOH value to assess paleotemperatures, as the composition of illite can be influenced by the composition of the host rocks or the hydrothermal fluid. In addition, values of the illite spectral maturity (ISM; ratio of the depth of the ~2,200 nm minima divided by the ~1,900 nm minima) can be affected by the presence of other hydrous minerals, quartz-sulfide veins, and absorption intensity (which can be a function of rock coloration). Despite these cautions, the spatial distribution and variation of the wAlOH and ISM values for illite suggest that the high paleotemperature hydrothermal upflow zones related to the Zhengguang Au-Zn deposit were located below ore zones I and IV, which are predicted to be proximal to the intrusive center of the system.
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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 | 0.001 |
| 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".