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Record W2914260430 · doi:10.1002/gj.3437

Geochemistry and mineral chemical behavior of hydrothermal alteration of the Tuwu porphyry copper deposit, Eastern Tianshan, Northwest China

2019· article· en· W2914260430 on OpenAlexaff
Hongqing Yuan, Ping Shen, Hongdi Pan, Zhi‐Hai An, Ge Ma, Wenguang Li

Bibliographic record

VenueGeological Journal · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsLaurentian University
FundersNational Key Research and Development Program of ChinaNational Natural Science Foundation of China
KeywordsGeochemistryGeologySericiteHydrothermal circulationDioriteMineralization (soil science)AlbiteChloritePorphyry copper depositMolybdeniteMineralogyFluid inclusionsQuartzZircon

Abstract

fetched live from OpenAlex

The Tuwu deposit is one of the largest porphyry copper deposits in the Eastern Tianshan, Northwest China. Ore bodies of the deposit are associated with the tonalite porphyry, which intruded the Early Carboniferous Qi´eshan Group. The hydrothermal ore‐forming processes include the porphyry mineralization episode with potassic, chlorite‐sericite/albite, phyllic, and propylitic alteration and the overprinting mineralization episode. These hydrothermal alteration episodes were studied on the basis of mass transfer and element mobility. The mass balance data and isocon diagrams reveal that Cu is highly associated with the chlorite‐sericite (albite) stage and followed by phyllic and potassic stages. On the basis of electron probe analysis, the SO3 contents of the igneous apatite from the tonalite porphyries range from 0.016 to 0.288 wt.%, which are higher than those from the diorite porphyries (SO3 = 0.088–0.179 wt.%). Similarly, the apatite saturation temperature (861–926°C) and magmatic S content (mean = 52.16 ppm) from the tonalite porphyries are also higher that from the diorite porphyries (T = 813–877°C; S = 28.25 ppm). These results suggest that the S content of the apatite is related to the temperature and S content of the melt. In the hydrothermal alteration zones, the F favours partitioning into apatite under lower temperature, the F contents of hydrothermal apatite increase from the potassic zones to the propylitic zones accompanying with the decrease of temperature. Cl element is much more sensitive to the pH, pressure, and fluid composition than F element. The Cl contents of the apatite increase from the potassic zones (0.18–0.46 wt.%) to the chorite‐sericite (albite) zones (0.28–0.58 wt.%), resulting from the decrease of fluid pH and pressure. The lower Cl contents of apatite (0.07–0.48 wt.%) in the phyllic zones were due to the lower Cl content of hydrothermal fluids. The highest Cl contents (0.09–0.69 wt.%) of apatite in the propylitic zones were caused by the decrease of pressure. The δ18Owater values of quartz in chlorite‐sericite (albite) zones and phyllic zones range from −0.8‰ to −0.4‰ and from −5.3‰ to 4.8‰, and the δD values vary from −57‰ to −47‰ and from −52‰ to −44‰, respectively. Gaseous compositions of the fluid inclusions in quartz are dominated by H2O with minor CO2, and the liquid compositions mainly consist of Na+ and Cl−. These data imply that the ore‐forming fluids belong to the H2O‐NaCl system and evolved from magmatic water to meteoric water in origin.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.083
Threshold uncertainty score0.165

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.006
GPT teacher head0.178
Teacher spread0.172 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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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Citations3
Published2019
Admission routes1
Has abstractyes

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