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Record W3107094538 · doi:10.1002/9781119521143.ch2

Boundary‐Layer Melts Entrapped as Melt Inclusions? The Case of Phosphorus‐ and CO <sub>2</sub> ‐Rich Spinel‐Hosted Melt Inclusions from El Hierro, Canary Islands

2020· other· en· W3107094538 on OpenAlexaff
Marc‐Antoine Longpré, John Stix, Nobumichi Shimizu

Bibliographic record

VenueGeophysical monograph · 2020
Typeother
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsMelt inclusionsSpinelOlivineInclusion (mineral)GeologyMineralogySilicateCrystal (programming language)GeochemistryChemical engineering

Abstract

fetched live from OpenAlex

Melt inclusions provide unique information on the volatile budgets and compositional diversity of magmatic systems, but are susceptible to synentrapment and postentrapment compositional modifications. The possible formation of chemically anomalous boundary layers around growing crystals and their subsequent entrapment as melt inclusions have been demonstrated experimentally and theoretically, but are thought to be of negligible importance in natural melt-inclusion suites. Here we report on the major, trace, and volatile element compositions of spinel-hosted melt inclusions from El Hierro, Canary Islands, that show anomalous departures in FeOt–SiO2 space and high concentrations of P2O5, a slow diffuser in silicate melts, with respect to olivine-hosted melt inclusions, the matrix glass, and bulk rock from the same samples. These inclusions also display extremely high CO2 concentrations and high S/H2O and Cl/F ratios. With the rapid growth textures of spinels, these observations suggest that spinel-hosted melt inclusions represent boundary-layer melts, the compositions of which were controlled by synentrapment crystal growth and incomplete diffusive relaxation. Our results document a rare case of entrapment of boundary-layer melt in natural magmas, indicate that fast-grown spinel may be a poor melt-inclusion host target, and highlight a means to flag potential boundary-layer melts in melt-inclusion data sets.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
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 head0.008
GPT teacher head0.215
Teacher spread0.207 · 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 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

Citations3
Published2020
Admission routes1
Has abstractyes

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