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Scheelite texture and composition fingerprint skarn mineralization of the giant Yuku Mo-W deposit, Central China

2024· article· en· W4404626243 on OpenAlexaff
Yu Fan, Qihai Shu, David R. Lentz, Qingfei Wang, Rongzhen Zhang, Xudong Niu, Qingwen Zeng, Kai Xing, Jun Deng

Bibliographic record

VenueOre Geology Reviews · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsSkarnScheeliteGeologyMineralization (soil science)GeochemistryMineralogyFluid inclusionsHydrothermal circulationMetallurgyPaleontologyTungstenMaterials science

Abstract

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• The scheelite REE pattern is controlled by substitution mechanisms and affected by REE-bearing mineral coprecipitation. • The scheelite Eu anomaly can be used to assess fluid oxygen fugacity. • The scheelite Mo concentration should be used with other parameters to assess fluid oxygen fugacity. • The scheelite Mo concentration is valuable for distinguishing between orogenic and skarn deposits. Scheelite is widely used to reveal ore-forming redox environments and track hydrothermal evolution processes in W-bearing deposits. Yuku, situated in Central China, is a typical skarn Mo-W deposit discovered recently in the Luanchuan Mo-W-Zn-Pb ore district. This study determined the compositions of the Yuku scheelite via laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) and electron microprobe analysis (EMPA) techniques. Based on the textural characteristics and mineral assemblages, three types of scheelite were categorized, including Sch A1, Sch A2, and Sch B. In general, Sch A1 formed during the prograde stage, mostly occurring as euhedral grains that distributed discretely within the interstices of skarn minerals. Sch A2 predominantly formed as the rim of Sch A1 or crosscut Sch A1. It is commonly associated with sulfides, such as pyrrhotite, pyrite, and molybdenite. Sch B is primarily observed in the quartz-sulfide veins or within pyrrhotite crystals, occurring later than Sch A1 and Sch A2. Geochemically, Sch A1 contains a significantly higher Mo content (>14,300 ppm) and is characterized by a negative inclined chondrite-normalized rare earth element (REE) pattern, while Sch B has Mo contents lower than 10,300 ppm and exhibits an M-type tetrad REE pattern. Sch A2 contains a Mo content ranging from 146 ppm to 89,000 ppm (mean 27,900 ppm) and displays an intricate REE pattern that partially overlaps with Sch A1 and Sch B. The difference of REE concentrations among different scheelite generations is controlled by substitution mechanisms and also influenced by the precipitation of garnet and pyroxene. Sch A1 and Sch B exhibit a linear 1:1 trend between Na (atom) and ΣREE – Eu + Y (atom), indicating the important role of substitution via 2Ca 2+ = REE 3+ + Na + . The concentrations of Nb, Ta and V are notably low, supporting only a small amount of REE incorporation into Sch A1 through Ca 2+ + W 6+ = REE 3+ + (Nb + Ta + V) 5+ . The REE patterns of Sch A1 and partly Sch A2 resemble those of the causative intrusions, indicating that substituting the site vacancy in scheelite lattice is another crucial mechanism. All three substitution mechanisms play roles in REE incorporation during the scheelite mineralization process. Negative Eu anomalies prevail in Yuku scheelite (mean δEu = 0.77), although positive Eu anomalies are also observed, particularly in Sch B (mean δEu = 1.11). Additionally, there is a conspicuous decreasing trend in the Mo content from the prograde to late stage, suggesting that the Mo-W mineralization at Yuku likely experienced a decrease in oxygen fugacity and/or temperature. Furthermore, in a comparative analysis of scheelite Mo content and Eu anomaly with other deposits, it was observed that Mo content in skarn deposits is generally higher than that in orogenic deposits (mostly <100 ppm), providing a tool for distinguishing deposit types utilizing scheelite geochemical characteristics.

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How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.094
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.008
GPT teacher head0.202
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

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Citations4
Published2024
Admission routes1
Has abstractyes

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