A New Zincian Greenockite Occurrence in the Saishitang Cu Skarn Deposit, Qinghai Province, Northwest China
Bibliographic record
Abstract
Zn-Cd-S series minerals not only comprise industrial resources for Zn and Cd, but are also significant mineralogical indicators for hydrothermal ore-forming processes. Due to its unique formation conditions and rare occurrence, our understanding of the formation of zincian greenockite in natural systems is limited. Zincian greenockite was discovered during mineralogical studies in the Saishitang Cu skarn deposit, Qinghai Province, Northwest China. This provided an ideal opportunity to assess the occurrence and formation of zincian greenockite in skarn-type deposits. Ore minerals were observed using reflected-light microscopy, and the zincian greenockite was further analyzed using electron-probe microanalysis (EPMA) and X-ray diffraction (XRD). The zincian greenockite occurs in the bornite–chalcopyrite ores and is composed of subhedral to anhedral grains approximately 50 × 150 μm2 to 200 × 300 μm2 in size, replaces the bornite, and is replaced by native silver. Two phases (I and II) were identified based on back-scattered electron images, X-ray element-distributions maps, and EPMA data. The textural relationship indicated that Phase I was replaced by Phase II. Phase I contained high Zn (14.6 to 21.7 mol % ZnS) and low Cd (72.4 to 82.2 mol % CdS), while Phase II contained low Zn (5.6 to 9.1 mol % ZnS) and high Cd (85.4 to 89.9 mol % CdS). The zincian greenockite was formed at temperature of 300~270 °C during the transformation from a reducing environment to an oxidizing one in the late stage of the mineralization process in the Saishitang deposit.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".