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Record W3001266365 · doi:10.3390/min10020096

An Experimental Investigation of Interaction between Andesite and Hyperacidic Volcanic Lake Water

2020· article· en· W3001266365 on OpenAlexafffund
Vincent van Hinsberg, Kim Berlo, Jacob B. Lowenstern

Bibliographic record

VenueMinerals · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaU.S. Geological SurveyUnited States Agency for International Development
KeywordsGeologyScoriaGeochemistryLavaPlagioclaseAugiteVolcanic glassPhenocrystAndesiteMagmaMineralogyLava domePetrologyVolcanoVolcanic rockQuartz

Abstract

fetched live from OpenAlex

Alteration in magmatic-hydrothermal systems leads to distinct changes in rock texture and mineralogy, and a strong redistribution of elements between fluid and rock. Here, we experimentally interacted andesite scoria with hyperacidic, high-sulfidation style fluids from Kawah Ijen volcano (Indonesia) at 25 and 100 °C, seeking to reproduce the textures observed in natural samples from this volcano, and to understand the element fluxes that accompany alteration. The susceptibility to alteration in the experiments is Cu–Fe-sulphide > calcic plagioclase > pyroxene > titano-magnetite > sodic plagioclase, with complete preservation of glass. Silicate minerals alter to opaline silica, and gypsum, barite and a Zr-phase precipitate. The selective alteration of the phenocryst minerals results in a preferential release of compatible elements, as the glass is the main incompatible element host. The experiments reproduce the alteration textures of the natural samples, including the preservation of glass, but the predicted compatible over incompatible element enrichment in the alteration element flux is not observed in the natural setting. This suggests that alteration at Kawah Ijen is dominated by lithologies that lack abundant glass, in particular lava flows where the glass has devitrified, despite these lava flows having a lower surface area compared to scoria.

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)0.000
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.270
Threshold uncertainty score0.996

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)0.0050.000

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 head0.032
GPT teacher head0.230
Teacher spread0.198 · 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 designBench or experimental
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

Citations6
Published2020
Admission routes2
Has abstractyes

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