Geochronological and sulfide geochemical evidence for gold mineralization related to post-collisional magmatism in the Wulonggou goldfield of the East Kunlun Orogen, northern Tibet
Bibliographic record
Abstract
The relationships among magmatism, orogeny, and gold mineralization in lode gold deposits have been controversial for a long time. The East Kunlun Orogen in northern Tibet has experienced a complex Paleo-Tethyan tectono-magmatic evolution and hosts the largest Wulonggou lode gold deposits (>120 t). The Shuizhadonggou-Huanglonggou (SZDG-HLG) gold deposit is the largest in the Wulonggou goldfield and is an excellent candidate for solving the controversy through detailed field observations, magmatic and hydrothermal mineral in-situ U-Pb dating, and gold-bearing sulfide in-situ trace elements and sulfur-lead isotopes. Gold mineralization in the SZDG-HLG deposit includes sulfide disseminations and minor amounts of small quartz-sulfide veins in hydrothermal alteration assemblages along a ductile shear zone. Gold mineralization can be divided into four stages based on crosscutting relationships and associated alteration assemblages. U-Pb ages from magmatic zircon, hydrothermal rutile, and hydrothermal monazite support field relationships that gold mineralization was later than the ductile deformation but synchronous with the post-collisional porphyries. Gold mineralization evolved from high to low temperatures (560℃ to less than 300℃), accompanied by markedly decreased sulfur fugacities (–6.3 to –12.5) and oxygen fugacities (–20.7 to –40.5). The gradual increase of sulfur isotopes (δ34S) from stage 1 (–0.9 to 1.8 ‰ in Py1a) to stage 3 (up to 8 ‰) is ascribed to sulfide precipitation from a finite fluid reservoir, while the sharp decrease of δ34S values in stage 4 (down to –24 ‰) is caused by the fluid oxidation. The negative covariations of δ34S and Se/S values, positive correlations between Au and chalcophile elements (As, Sb, Te, and Bi) in most sulfides, and overlapping lead isotopes of sulfides and Late Triassic granodiorite-diorite confirm a post-collisional magmatic gold and sulfur source. This study demonstrates that lode gold deposits in Phanerozoic orogens having similar characteristics to their counterparts in Archean metamorphic terranes can be genetically related to post-collisional magmatism.
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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 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".