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Record W3031367548 · doi:10.1038/s41598-020-65226-3

Melt inclusion vapour bubbles: the hidden reservoir for major and volatile elements

2020· article· en· W3031367548 on OpenAlexaff
Swetha Venugopal, Federica Schiavi, Séverine Moune, Nathalie Bolfan‐Casanova, T. H. Druitt, Glyn Williams‐Jones

Bibliographic record

VenueScientific Reports · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsSimon Fraser University
FundersAgence Nationale de la Recherche
KeywordsMelt inclusionsMineralogyBubbleOlivineRaman spectroscopyInclusion (mineral)DiffusionBasaltAnhydriteMagmaCrystalliteAnalytical Chemistry (journal)GypsumGeologyMaterials scienceChemical engineeringChemistryGeochemistryThermodynamicsMetallurgyEnvironmental chemistryVolcano

Abstract

fetched live from OpenAlex

Abstract Olivine-hosted melt inclusions (MIs) provide samples of magmatic liquids and their dissolved volatiles from deep within the plumbing system. Inevitable post-entrapment modifications can lead to significant compositional changes in the glass and/or any contained bubbles. Re-heating is a common technique to reverse MI crystallisation; however, its effect on volatile contents has been assumed to be minor. We test this assumption using crystallised and glassy basaltic MIs, combined with Raman spectroscopy and 3D imaging, to investigate the changes in fluid and solid phases in the bubbles before and after re-heating. Before re-heating, the bubble contains CO2gas and anhydrite (CaSO4) crystallites. The rapid diffusion of major and volatile elements from the melt during re-heating creates new phases within the bubble: SO2, gypsum, Fe-sulphides. Vapour bubbles hosted in naturally glassy MIs similarly contain a plethora of solid phases (carbonates, sulphates, and sulphides) that account for up to 84% of the total MI sulphur, 80% of CO2, and 14% of FeO. In both re-heated and naturally glassy MIs, bubbles sequester major and volatile elements that are components of the total magmatic budget and represent a “loss” from the glass. Analyses of the glass alone significantly underestimates the original magma composition and storage parameters.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 head0.020
GPT teacher head0.221
Teacher spread0.200 · 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".

Quick stats

Citations70
Published2020
Admission routes1
Has abstractyes

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