Protolith-Related Thermal Controls on the Decoupling of Sn and W in Sn-W Metallogenic Provinces: Insights from the Nanling Region, China
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Bibliographic record
Abstract
Abstract The Nanling region of South China hosts the largest W-Sn metallogenic province in the world, accounting for more than 54% of global tungsten resources as well as important resources of tin and rare metals. An important feature of this province, which is shared by a number of other W-Sn metallogenic provinces, is that W deposits occur separately from Sn and Sn-W deposits, with the latter concentrated in the western part of the region (especially along the deep, NE-trending Chenzhou-Linwu fault) and the W deposits to the east of them. All the deposits are associated with ilmenite series, peraluminous granites. However, the granites associated with the Sn and Sn-W deposits can be distinguished from the W granites by their higher bulk-rock εNd values and their higher zircon εHf values. Most importantly, the Sn and Sn-W granites are characterized by higher zircon saturation temperatures (800 ± 20°C) than the W granites (650°–750°C). The Sn and Sn-W granites also contain abundant mantle-derived mafic microgranular enclaves, whereas such enclaves are rare in the W granites. A model is proposed in which the protolith to the W granites released W to the melt as a result of the breakdown of muscovite. The temperature of melting, however, was too low for biotite to melt. In the west, particularly along the Chenzhou-Linwu fault (the location of the Sn and Sn-W deposits), higher temperatures enabled the breakdown of both muscovite and biotite and the consequent release of both Sn and W to form Sn and Sn-W granites. This model, which is based on differences in the protolith melting temperature and thus mobilization temperatures for Sn and W, is potentially applicable to any Sn-W metallogenic province in which the Sn and Sn-W deposits are spatially separated from the W deposits.
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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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it