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Record W4321489942 · doi:10.5194/egusphere-egu23-4047

Drilling and monitoring in Hyuga-Nada: Unveiling effects of ridge subduction on slow earthquakes

2023· preprint· en· W4321489942 on OpenAlexaff
Masataka Kinoshita, Rie Nakata, Yoshitaka Hashimoto, Yohei Hamada, Laura Wallace, Tianhaozhe Sun, Eiichiro Araki, Yusuke Yamashita

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsGeological Survey of Canada
Fundersnot available
KeywordsGeologySeamountSubductionSeismologyDrillingPaleontologyTectonics

Abstract

fetched live from OpenAlex

Shallow slow earthquakes, which last minutes to years, are important indicators of subduction megathrust slip behavior and future seismic and tsunami potential. Subducting plate roughness and seamounts have been proposed to promote slow earthquakes by inducing local geomechanical and hydrogeological anomalies. The Hyuga-Nada region offshore Kyushu, Japan is an outstanding locale for drilling and observatory experiments to investigate these effects. In this region, slow earthquakes are repeatedly observed on and near the subducting Kyushu-Palau-Ridge, KPR, chain of seamounts thus providing excellent opportunities to explore the effects of seamounts on geomechanical/hydrological/thermal properties, and ultimately seismic coupling. Long-term monitoring enabled by a planned permanent network (N-net) will allow subsurface processes during frequent (~1 year) periodical slow earthquakes and ~M7 earthquakes (~20-30 year interval) to be captured with high fidelity. Drilling, logging, and coring will provide key constraints on stress state, hydrological processes, and sediment physical properties in the region above the ridge. We have originally proposed the drilling and monitoring plan to IODP in 2019 (Nakata et al. 2019). In this presentation, we report the updated proposal plan along with initial processing results of new site survey data acquired with JAMSTEC (Miura et al., 2021, Arai et al., 2021, Ma et al., 2021). We propose to drill and install observatories at three primary locations in Hyuga-Nada to address two hypotheses: 1) Seamount subduction modulates stress and pore pressure, creates fracture networks and influences the thermal and hydrological state of the margin. 2) The spatiotemporal distribution of slow earthquakes is strongly influenced by seamount subduction through the processes outlined in Hypothesis 1. We will drill three primary distinct sites relative to the seamount, to (1) measure physical properties, and (2) describe deformation by LWD, APCT-3, and core analysis to characterize in-situ stress state, fracture density, heat flow, and pore fluid flow. Spatial variations in the upper plate disruption caused by seamount subduction will be revealed by comparing results from sites in the leading and lateral edges, and top of the currently subducting seamount; and these will constrain geomechanical, hydrological, and thermal models. At two of the sites, we will install a “Fiber-CORK” observatory equipped with conventional pressure and temperature sensors and cutting-edge fiber-optic sensors. One site may be connected to the N-net node for real-time data streaming. The combination will fill a gap in slip durations currently observable in this region with seismic and geodetic instrumentation. Fully characterizing slow earthquakes will reveal the degree to which they accommodate plate motion, and whether strain is accumulated for future earthquakes.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.079
Threshold uncertainty score0.158

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.033
GPT teacher head0.240
Teacher spread0.206 · 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

Citations0
Published2023
Admission routes1
Has abstractyes

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