MétaCan
Menu
Back to cohort
Record W4375853156 · doi:10.1130/g51169.1

Mantle wedge olivine modifies slab-derived fluids: Implications for fluid transport from slab to arc magma source

2023· article· en· W4375853156 on OpenAlexaff
Jan C.M. De Hoog, Eleri Clarke, Kéiko Hattori

Bibliographic record

VenueGeology · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geochemical Analysis
Canadian institutionsUniversity of Ottawa
FundersNatural Environment Research CouncilSight Research UK
KeywordsOlivineGeologyMantle wedgeMantle (geology)SlabPeridotiteSubductionGeochemistryDiapirPetrologyTransition zoneGeophysicsTectonicsSeismology

Abstract

fetched live from OpenAlex

Abstract Boron is an effective tracer of fluid processes in subduction zones. High B and δ11B in arc magmas require efficient B transfer from the slab to magma source regions. The Higashi-akaishi metaperidotite body in the Sanbagawa high-pressure belt, Japan, is composed of locally serpentinized mantle wedge peridotites exhumed in a subduction channel. Cores of coarse-grained primary mantle olivine have 1–4 µg/g B, enriched compared to typical mantle olivine, and δ11B of −10‰ to −1‰, consistent with incorporation of fluids from dehydrating slab at ~90–120 km depth. Rims of primary mantle olivine as well as olivine neoblasts have even higher B (5–20 µg/g) and higher δ11B (−8‰ to +2‰) due to incorporating slab fluids at depths of ~70–100 km. Antigorite, formed below 650 °C, shows comparable δ11B and B contents as olivine rims. The data show that olivine is capable of scavenging significant amounts of B from fluids by diffusion and recrystallization at sub-arc pressures and temperatures. Considering the large amount of olivine in the mantle wedge, transport of slab-derived material to magma sources requires processes with minimal interaction with mantle peridotite, such as intensely channelized fluid flow or ascent of mélange diapirs, and limited porous fluid flow.

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 categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.058
Threshold uncertainty score0.998

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)0.0090.003

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 head0.023
GPT teacher head0.225
Teacher spread0.201 · 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; both teacher heads agree on what is shown here.

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

Citations11
Published2023
Admission routes1
Has abstractyes

Explore more

Same venueGeologySame topicGeological and Geochemical AnalysisFrench-language works237,207