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Record W3012585342 · doi:10.2138/am-2020-7226

Zircon and Apatite Geochemical Constraints on the Formation of the Huojihe Porphyry Mo Deposit in the Lesser Xing’an Range, NE China

2019· article· en· W3012585342 on OpenAlexaff
Kai Xing, Qihai Shu, David R. Lentz, Fangyue Wang

Bibliographic record

VenueAmerican Mineralogist · 2019
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsZirconGeologyGeochemistryApatiteChinaRange (aeronautics)MineralogyArchaeologyMaterials scienceGeography

Abstract

fetched live from OpenAlex

Northeastern China is an important Mo resource region in China, with more than 80 Mo deposits and occurrences. The Huojihe deposit located in the Lesser Xing’an Range represents one of the many Mesozoic porphyry Mo deposits in NE China and has been selected for investigation attempting to clarify the possible mechanisms controlling Mo mineralization. In this study, accessory minerals, including zircon and apatite from the causative intrusions (biotite monzogranite and granodiorite), have been analyzed to reveal their chemical and isotopic compositions, which provide insights into the nature of the source magmas and a better understanding of the factors affecting their mineralization potential. Zircon U-Pb dating shows that the biotite monzogranite from the Huojihe deposit formed at 181.6 ± 0.6 Ma, which is identical to the previously reported molybdenite Re-Os age (~181 Ma), indicating that the Mo mineralization is probably genetically related to the intrusion. The intrusion samples share homogeneous geochemical and Sr-Nd isotopic compositions, with initial 87 Sr/ 86 Sr ratios of 0.7072–0.7075 and slightly negative ε Nd (t) values from –2.3 to –1.4, reflecting a uniform magma source. The least-altered apatites show similar (or slightly enriched) initial 87 Sr/ 86 Sr ratios (0.7080–0.7108) and ε Nd (t) values (–4.0 to –1.8), whereas the hydrothermally altered apatites are characterized by significantly higher initial 87 Sr/ 86 Sr ratios (0.7091–0.7119) and more negative ε Nd (t) values (–4.9 to –4.4), probably due to the interaction between the hydrothermal fluids and wall rocks. The zircon ε Hf (t) values vary from –0.9 to 1.7, corresponding to a restricted range of T DM2 ages from 1279 to 1120 Ma. The Sr-Nd-Hf isotope results suggest that the primary magmas associated with the Mo mineralization could be generated from a dominantly Mesoproterozoic lower crust source, with rare contributions from the depleted mantle. The low Ga and Ce and high Eu contents in the magmatic apatite demonstrate that the original magmas have a relatively high oxygen fugacity, which is also supported by the high zircon Ce N /Ce N * (22–568) and Eu N /Eu N * (0.38–0.71) values. Estimates of absolute sulfur concentrations in the mineralization-related melt using available partitioning models for apatite return relatively low magmatic sulfur concentrations in Huojihe (20–100 ppm), indistinguishable from those of larger or smaller deposits or even barren magmatic bodies. Using the sulfur concentration data, a minimum volume of 10–50 km 3 magma has been suggested to be necessary to produce the Huojihe Mo deposit based on mass balance modeling. Besides, the Mo concentration in the original magma has also been roughly estimated based on the magma size (10–50 km 3 ) and the contained Mo in Huojihe (0.275 Mt). The magmatic Mo concentrations (2–10 ppm) are similar to many other porphyry Mo systems (e.g., the Climax-type porphyry Mo deposits), and are also comparable to subeconomic to barren magma systems. This study suggests that pre-degassing enrichments of Mo and S in the original magma is not necessarily important in the formation of the Huojihe Mo deposit; rather, factors other than melt composition may be more critical in forming a porphyry Mo deposit. This understanding might also apply to other porphyry Mo mineralized systems worldwide.

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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 score0.031
Threshold uncertainty score0.061

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 studies0.0010.000
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 head0.009
GPT teacher head0.193
Teacher spread0.184 · 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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Citations82
Published2019
Admission routes1
Has abstractyes

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