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Record W4404298568 · doi:10.1038/s43247-024-01864-z

Fluid upwelling across the Hikurangi subduction thrust during deep slow-slip earthquakes

2024· article· en· W4404298568 on OpenAlexafffund
Pasan Herath, Pascal Audet

Bibliographic record

VenueCommunications Earth & Environment · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Ottawa
KeywordsSubductionGeologyUpwellingSeismologyEpisodic tremor and slipThrustSlip (aerodynamics)OceanographyTectonics

Abstract

fetched live from OpenAlex

Abstract Slow-slip events at global subduction zones relieve tectonic stress over days to years. Through slow-slip cycles, high fluid pressures observed at the top of subducting plates are thought to fluctuate, potentially due to the valving action of an impermeable layer near the plate interface. We model teleseismic scattering data at the Manawatu deep slow-slip patch at the Hikurangi margin in New Zealand and find high seismic P-to-S wave velocity ratios, V P /V S , in the upper ~5 km of the subducting Pacific Plate, reflecting sustained elevated fluid pressures that decrease during slow-slip and increase during inter-slow-slip periods. Within a ~ 3 km thick lower crustal layer of the overriding Australian Plate, decreasing V P /V S during inter-slow-slip periods reflects permeability reduction due to mineral precipitation. Increasing V P /V S during slow-slip reflects increasing permeability and crack density, facilitating upward fluid transfer through this layer. Our results suggest it acts as a valve to relieve high fluid pressures in the subducting slab.

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 categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.861
Threshold uncertainty score1.000

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 studies0.0020.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.003

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 head0.234
Teacher spread0.210 · 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 designOther design
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
Published2024
Admission routes2
Has abstractyes

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