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Record W2594943952 · doi:10.1002/2017gl072690

Subsidence at Cerro Prieto Geothermal Field and postseismic slip along the Indiviso fault from 2011 to 2016 RADARSAT‐2 DInSAR time series analysis

2017· article· en· W2594943952 on OpenAlexafffund
Sergey Samsonov, Wanpeng Feng, Yuri Fialko

Bibliographic record

VenueGeophysical Research Letters · 2017
Typearticle
Languageen
FieldEarth and Planetary Sciences
Topicearthquake and tectonic studies
Canadian institutionsNatural Resources Canada
FundersNational Aeronautics and Space AdministrationCanadian Space AgencyNational Science Foundation
KeywordsGeologyInterferometric synthetic aperture radarSeismologyGeothermal gradientSlip (aerodynamics)GeodesyFault (geology)SubsidenceSynthetic aperture radarGeomorphologyGeophysicsRemote sensingStructural basin

Abstract

fetched live from OpenAlex

Abstract We present RADARSAT‐2 Differential Interferometric Synthetic Aperture Radar (DInSAR) observations of deformation due to fluid extraction at the Cerro Prieto Geothermal Field (CPGF) and afterslip on the 2010 M7.2 El Mayor‐Cucapah (EMC) earthquake rupture during 2011–2016. Advanced multidimensional time series analysis reveals subsidence at the CPGF with the maximum rate greater than 100 mm/yr accompanied by horizontal motion (radial contraction) at a rate greater than 30 mm/yr. During the same time period, more than 30 mm of surface creep occurred on the Indiviso fault ruptured by the EMC earthquake. We performed inversions of DInSAR data to estimate the rate of volume changes at depth due to the geothermal production at the CPGF and the distribution of afterslip on the Indiviso fault. The maximum coseismic slip due to the EMC earthquake correlates with the Coulomb stress changes on the Indiviso fault due to fluid extraction at the CPGF. Afterslip occurs on the periphery of maximum coseismic slip areas. Time series analysis indicates that afterslip still occurs 6 years after the earthquake.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.024
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

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

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 head0.026
GPT teacher head0.275
Teacher spread0.249 · 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

Citations25
Published2017
Admission routes2
Has abstractyes

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