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Ground Penetrating Radar for Environmental Applications

2001· article· en· W2152612388 on OpenAlexaff
Rosemary Knight

Bibliographic record

VenueAnnual Review of Earth and Planetary Sciences · 2001
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsGround-penetrating radarHydrogeologyGeologyRadarRemote sensingSubsurface flowPermeability (electromagnetism)Environmental scienceSoil scienceGroundwaterGeotechnical engineeringComputer science

Abstract

fetched live from OpenAlex

▪ Abstract Ground penetrating radar (GPR) is a near-surface geophysical technique that can provide high resolution images of the dielectric properties of the top few tens of meters of the earth. In applications in contaminant hydrology, radar data can be used to detect the presence of liquid organic contaminants, many of which have dielectric properties distinctly different from those of the other solid and fluid components in the subsurface. The resolution (approximately meter-scale) of the radar imaging method is such that it can also be used in the development of hydrogeologic models of the subsurface, required to predict the fate and transport of contaminants. GPR images are interpreted to obtain models of the large-scale architecture of the subsurface and to assist in estimating hydrogeologic properties such as water content, porosity, and permeability. Its noninvasive capabilities make GPR an attractive alternative to the traditional methods used for subsurface characterization.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.074
Threshold uncertainty score0.246

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0740.048

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 head0.016
GPT teacher head0.257
Teacher spread0.242 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations209
Published2001
Admission routes1
Has abstractyes

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