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A gravity gradient method for characterizing the post-seismic deformation field for a finite fault

2008· article· en· W2106099674 on OpenAlexaff
T. Hayes, K. F. Tiampo, José Fernández, John B. Rundle

Bibliographic record

VenueGeophysical Journal International · 2008
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsWestern University
Fundersnot available
KeywordsBouguer anomalyGeologyGravity anomalyFree-air gravity anomalyGeophysicsGeodesySeismologyGravitational fieldDeformation (meteorology)Slip (aerodynamics)Fault (geology)PhysicsClassical mechanics

Abstract

fetched live from OpenAlex

Gravity gradients are an effective method for delineating the extent of subsurface density anomalies. The change in subsurface density contrasts due to the seismic deformation gives rise to detectable gravity changes via the dilatational gravity signal or Bouguer anomaly. Solutions for the corresponding gravity gradients of these signals are developed for a vertical strike-slip fault. Gravity gradient solutions exhibit similar spatial distributions as those calculated for Coulomb stress changes, reflecting their physical relationship to the stress changes. The signals' magnitudes, of the order of 10−4 E, are beyond the resolution of typical exploration instruments. Improvements to Superconducting Gravity Gradiometers are necessary for gravity gradients to be used as a viable method for the observation of the stress field changes over large spatial scales.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.925
Threshold uncertainty score0.444

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.024
GPT teacher head0.268
Teacher spread0.244 · 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 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

Citations8
Published2008
Admission routes1
Has abstractyes

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