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Record W4327724889 · doi:10.1130/g50893.1

Melt inclusion evidence for limestone assimilation, calc-silicate melts, and “magmatic skarn”

2023· article· en· W4327724889 on OpenAlexafffund
Xinyue Xu, Xiaochun Xu, Marko Szmihelsky, Jun Yan, Qiaoqin Xie, Matthew Steele‐MacInnis

Bibliographic record

VenueGeology · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of Alberta
FundersChina Scholarship CouncilNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsSilicateGeologyMelt inclusionsGeochemistryCarbonateSkarnMineralogyIgneous rockCarbonatiteSilicate mineralsMantle (geology)Fluid inclusionsChemistryHydrothermal circulation

Abstract

fetched live from OpenAlex

Abstract Chemical exchange between silicate magmas and carbonate rocks has major implications for igneous fractionation, atmospheric CO2 flux, and formation of mineral deposits. However, this process is only partly understood, and long-standing questions of whether, where, and how carbonate rocks can be digested by silicate melts remain controversial. We describe evidence for pervasive chemical exchange between silicate melt and carbonate rock in a shallow porphyry setting driven by limestone assimilation. Melt inclusions in endoskarn from the Chating Cu-Au deposit in eastern China reveal that the calc-silicate assemblage (diopside + andradite ± wollastonite ± epidote) was molten at the time of skarn formation and coexisted with CO2 vapor as well as sulfate- and chloride-salt melts. Hence, we argue that endoskarn at Chating formed by crystallization of an immiscible calc-silicate melt produced by assimilation of carbonate rock, aided by the presence of sulfate and other fluxes, which in turn promoted desilication of the intruding magma and drove vigorous CO2 release.

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 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)0.001
metaresearch head score (Gemma)0.001
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 score0.166
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0020.000

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 head0.051
GPT teacher head0.283
Teacher spread0.231 · 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".

Quick stats

Citations16
Published2023
Admission routes2
Has abstractyes

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