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Record W4375853656 · doi:10.1130/g50867.1

A mechanism for transient creep in crustal shear zones

2023· article· en· W4375853656 on OpenAlexaff
Christopher A. Thom, J. D. Kirkpatrick

Bibliographic record

VenueGeology · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsMcGill University
Fundersnot available
KeywordsCreepGeologySlip (aerodynamics)BrittlenessShear (geology)Dislocation creepShear zoneShearing (physics)Strain rateDislocationSeismologyGeotechnical engineeringMechanicsPetrologyMaterials scienceTectonicsComposite materialThermodynamics

Abstract

fetched live from OpenAlex

The brittle-to-ductile transition in faults and shear zones marks the change from frictional stick-slip behavior in the seismogenic zone to creep accommodated by plastic mechanisms at higher temperatures. Geodetic observations of slow slip events (SSEs) on plate-boundary shear zones indicate that transient periods of elevated aseismic slip rate occur beneath the seismogenic zone where dislocation creep is likely to be active. SSE duration on the San Andreas fault (California, USA) and major subduction zones decreases systematically with increasing depth and temperature. However, current flow laws for dislocation creep are unable to explain the occurrence of transients similar to SSEs. We develop a microphysical model of dislocation creep that shows how small perturbations in stress (of the order kPa) can lead to strain-rate transients orders of magnitude faster than the background during nominally steady-state flow. The model explains the first-order characteristics of SSEs, reconciling the geophysical observations of deep slow slip events with expectations from experimental rock mechanics. Given that these microphysical mechanisms are general to rock-forming silicate minerals, our results suggest that non-steady-state deformation is inherent to natural shear zones that deform by dislocation creep and that the transition from brittle to steady-state creep occurs over a broad depth range within which transients are predominant.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.197
Threshold uncertainty score0.990

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)0.0010.000

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 head0.025
GPT teacher head0.233
Teacher spread0.208 · 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 teacher head, 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

Citations6
Published2023
Admission routes1
Has abstractyes

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