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Record W1991296426 · doi:10.1002/2014gl060595

Spatiotemporal analysis and interpretation of 1993–2013 ground deformation at Campi Flegrei, Italy, observed by advanced DInSAR

2014· article· en· W1991296426 on OpenAlexafffund
Sergey Samsonov, K. F. Tiampo, Antonio G. Camacho, José Fernández, Pablo J. González

Bibliographic record

VenueGeophysical Research Letters · 2014
Typearticle
Languageen
FieldEngineering
TopicSynthetic Aperture Radar (SAR) Applications and Techniques
Canadian institutionsWestern UniversityNatural Resources Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsGeologyCalderaVolcanoSeismologyGeodesySubsidenceInterferometric synthetic aperture radarDeformation (meteorology)Synthetic aperture radarRemote sensingGeomorphologyStructural basin

Abstract

fetched live from OpenAlex

Abstract Campi Flegrei is one of the most hazardous volcanic areas in the world because of its close proximity to the city of Naples. Here we apply the multidimensional small baseline subset (MSBAS) differential interferometric synthetic aperture radar (DInSAR) technique to obtain vertical and horizontal components of ground deformation for Campi Flegrei at high spatial and temporal resolutions that span, for the first time, 20 years. The area underwent continuous subsidence from 1993 through 1999. Moderate uplift began in 2010 and substantially increased through 2012, reaching approximately 13 cm by 2013. We model the observed deformation to determine source parameters for subsidence and uplift epochs. Both the inflation and deflation mechanisms involve large, extended sources in a layered hydrothermal system whose location is controlled by the caldera structure and stratigraphy. The temporal resolution of MSBAS approaches that of GPS daily time series, with superior precision and spatial resolution, making it an excellent alternative for volcano monitoring.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.829
Threshold uncertainty score0.481

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.014
GPT teacher head0.265
Teacher spread0.250 · 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 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

Citations40
Published2014
Admission routes2
Has abstractyes

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