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Record W1976863828 · doi:10.1029/2005jb004092

Gravity changes from a stress evolution earthquake simulation of California

2006· article· en· W1976863828 on OpenAlexaff
T. Hayes, K. F. Tiampo, John B. Rundle, José Fernández

Bibliographic record

VenueJournal of Geophysical Research Atmospheres · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsWestern University
Fundersnot available
KeywordsGeologyGeodesySeismologySlip (aerodynamics)Fault (geology)SIGNAL (programming language)PhysicsComputer science

Abstract

fetched live from OpenAlex

The gravity signal contains information regarding changes in density at all depths and can be used as a proxy for the strain accumulation in fault networks. A stress evolution time‐dependent model was used to create simulated slip histories over the San Andreas Fault network in California. Using a linear sum of the gravity signals from each fault segment in the model, via coseismic gravity Green's functions, a time‐dependent gravity model was created. The steady state gravity from the long‐term plate motion generates a signal over 5 years with magnitudes of ±∼2 μGal; the current limit of portable instrument observations. Moderate to large events generate signal magnitudes in the range of ∼10 to ∼80 μGal, well within the range of ground‐based observations. The complex fault network geometry of California significantly affects the spatial extent of the gravity signal from the three events studied.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.690

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.030
GPT teacher head0.291
Teacher spread0.261 · 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 designSimulation or modeling
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

Citations17
Published2006
Admission routes1
Has abstractyes

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