Metallogeny in the Bangong–Nujiang belt, central Tibet, China: A review
Bibliographic record
Abstract
The Bangong–Nujiang metallogenic belt consists of scattered Tethyan oceanic blocks, mainly distributed underneath the margins of the Qiangtang and Lhasa terranes in central Tibet. A new world-class metallogenic belt has been reported in this region recently, based on the geological mapping and ore deposit prospecting over the last two decades. It currently comprises inferred resources of 30 Mt Cu and 500 t Au, together with several Cr–Ni, Fe, and W (Mo) resources, forming a significant potential area for future mineral exploration. These metals are mainly hosted in porphyry copper, skarn copper, skarn iron, orogenic gold, quartz-vein tungsten, and ophitic chromite deposits. The mineral deposits in the Bangong–Nujiang metallogenic belt have been widely recognized in different localities, including the southern edge of the southern Qiangtang block, part of the north Lhasa block, and even part of the central Lhasa block, indicating they were formed in variable geological settings, from the initial opening, subduction, and collision to the extension of the Bangong–Nujiang Ocean. Specifically, five major tectonic events contributed to mineralization, including the stage 1 (240–165 Ma) initial opening of the Bangong–Nujiang Ocean, stage 2 (165–145 Ma) oceanic subduction, stage 3 (145–100 Ma) close of the ocean, stage 4 (100–65 Ma) continent–continent collisional orogenesis, and stage 5 (65–0 Ma) post-orogenesis. At stage 1, Cr–Ni deposits were formed during the initial opening of the ocean; porphyry–epithermal Cu (Au), skarn Fe, and minor orogenic Au deposits were formed at stage 2 and stage 3; a younger pulse of a few porphyry–skarn Cu ± Mo and orogenic Au deposits were formed during stage 4; finally, W(Mo) deposits were generated in stage 5. In general, porphyry Cu systems, orogenic Au, and skarn Cu polymetallic deposits that occurred in the subduction and post-collision settings related W(Mo) deposits have the most potential for future exploration. An in-depth investigation of several scientific problems, such as addressing the tectonic setting, magmatism, and metallogeny of this region and genetic linkage of these deposit preservations to plateau uplift, is essential for the future success of exploration in the Bangong–Nujiang metallogenic 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".