Geochemistry of Pyrite from the Gangcha Gold Deposit, West Qinling Orogen, China: Implications for Ore Genesis
Bibliographic record
Abstract
Abstract The Gangcha gold deposit was discovered in 2011 in the Xiahe‐Hezuo region, West Qinling Orogen, China. Five types of pyrite have been identified in the ore according to the detailed mineral paragenetic studies. Geochemical data are presented for type I pyrite (py1) rim‐core zonation and for the different types of pyrite based on in‐situ laser ablation inductively coupled plasma mass spectrometry (LA‐ICP‐MS) and electron probe microanalysis (EPMA). The results show that pyrites are characterized with heterogeneous Au concentrations, which indicate that Au occurs mainly as micro‐ or nano‐particle native inclusions. Time‐resolved depth profiles demonstrate that As, Co and Ni occur as solid solutions in pyrite, whereas Cu, Pb, Zn and Ag occur mainly as inclusions. Trace element concentrations differ between rims and cores in py1, and the differences also exist within different pyrite types. These differences indicate complex chemical evolution of the ore‐forming fluids, and the overall geology, geochronology, and stable isotope and pyrite data suggest that the ore‐forming fluids were closely linked to magmatic activity during the Triassic Period in West Qinling orogenic belt.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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".