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Record W3119843760 · doi:10.1029/2020gl090853

Crustal Rotation and Fluids: Factors for the 2019 Ridgecrest Earthquake Sequence?

2021· article· en· W3119843760 on OpenAlexaff
Ping Tong, Jiayuan Yao, Qinya Liu, Tianjue Li, Kai Wang, Shaolin Liu, Yau‐Wing Cheng, Shucheng Wu

Bibliographic record

VenueGeophysical Research Letters · 2021
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsSinistral and dextralGeologySeismologyClockwiseShear (geology)Rotation (mathematics)AnisotropyFault (geology)Shear zoneForeshockGeodesyTectonicsGeometryPetrologyAftershockPhysics

Abstract

fetched live from OpenAlex

Abstract P‐wave azimuthal anisotropic tomography reveals that the July 6, 2019 Mw 7.1 Ridgecrest earthquake occurred in a region with clockwise crustal rotation. The rotation together with the sinistral slip on the Garlock Fault is a response to the northwest‐trending, dextral shear within the Eastern California Shear Zone due to the relative motion between the Pacific and North America Plates. The hypocentral area of the Ridgecrest mainshock is characterized by a sharp lateral velocity contrast which has a reversal in contrast polarity at about 5 km depth. We find high Vp/Vs ratio structures covering the rupture zones of the Mw 6.4 foreshock and the Mw 7.1 mainshock, which may indicate the existence of fluids in the fault zones. We speculate that fluids and crustal rotation may have played important mechanical roles in causing the 2019 Ridgecrest earthquake sequence.

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)0.003
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 score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.070
GPT teacher head0.311
Teacher spread0.242 · 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

Citations36
Published2021
Admission routes1
Has abstractyes

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