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Record W2890316842 · doi:10.1029/2018jb015638

Smoothing of Fault Slip Surfaces by Scale‐Invariant Wear

2018· article· en· W2890316842 on OpenAlexaff
Kélian Dascher-Cousineau, J. D. Kirkpatrick, Michele L. Cooke

Bibliographic record

VenueJournal of Geophysical Research Solid Earth · 2018
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsMcGill University
FundersGeological Society of America
KeywordsSlip (aerodynamics)GeometryGeologyAsperity (geotechnical engineering)Slip line fieldSurface finishScalingSmoothingSurface roughnessMaterials scienceGeotechnical engineeringShear (geology)Composite materialPetrologyPhysicsMathematics

Abstract

fetched live from OpenAlex

Abstract Previous field observations suggest that fault slip surface roughness may decrease with slip. However, measurements have yet to confidently isolate the effect of slip from other possible controls, such as lithology or tectonic setting. We describe the evolution of slip surfaces in normal faults in SE Utah that cut well‐sorted, high‐porosity sandstones and accommodated regional extension at 1‐ to 4‐km depth. Tight controls on fault offset and uniform tectonic history allowed us to isolate the effect of slip during early stages of faulting (0‐ to 55‐m slip). Slip surfaces progress from rough joints and deformation bands toward smooth, continuous, and mirror‐like surfaces with increasing slip. We collected 123 scans of pristine slip surfaces, which measure surface geometry from micrometers to meters in length scale. Results indicate that slip surface roughness is systematically smoother than joint surfaces and deformation band edges. Over the best resolved length scales (0.1–10 mm), we observe roughness decreases with slip according to a power law with exponent −1 in the slip direction. Slip‐perpendicular profiles, though rougher, exhibit the same smoothing trend. The Hurst scaling exponent does not change with slip. These observations require wear to be multiscale. Boundary element method models suggest that mechanical wear of completely mated surfaces occurs by asperity failure and that the wear rate depends on the aspect ratio of asperities. These results indicate that at large slip, asperity failure at all length scales can cause slip surfaces to smooth while maintaining the fractal geometry characteristic of faults.

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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.508
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.038
GPT teacher head0.320
Teacher spread0.282 · 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.

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

Citations21
Published2018
Admission routes1
Has abstractyes

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