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Record W2053479914 · doi:10.1109/icgpr.2010.5550223

Crosshole GPR traveltime tomography in elliptically anisotropic media

2010· article· en· W2053479914 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsInstitut National de la Recherche Scientifique
Fundersnot available
KeywordsVadose zoneGround-penetrating radarAnisotropyGeologyTomographyCovarianceSynthetic dataGeophysicsMineralogyAlgorithmComputer scienceOpticsGeotechnical engineeringMathematicsPhysicsGroundwaterStatistics

Abstract

fetched live from OpenAlex

Owing to relatively rapid water content variations with respect to electromagnetic wavelength at GPR frequencies, the vadose zone usually exhibits significant velocity anisotropy. Neglecting anisotropy in traveltime tomographic reconstruction leads to artifacts that can obscure important subsurface features, the vadose zone being subject to this problem. In this paper, an algorithm for crosshole GPR geostatistical traveltime tomography in elliptically anisotropic media is presented. The advantages of the geostatistical tomography algorithm are that the solution is regularized by the covariance of the model parameters and that stochastic simulations can be performed to appraise the variability of the solution space. The implementation relies on a fast curved raytracing scheme specifically crafted for the problem at hand. The benefits of the algorithm to image the vadose zone are illustrated through a synthetic case that is representative of typical studies in quaternary geological settings. The results show that considering anisotropy yields better fit to the data at high ray angles and reduces reconstruction artifacts.

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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score0.297

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 studies0.0000.000
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 head0.006
GPT teacher head0.223
Teacher spread0.217 · 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

Quick stats

Citations4
Published2010
Admission routes1
Has abstractyes

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