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Ground Penetrating Radar for Environmental Applications

2001· article· en· W2152612388 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

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.984
Threshold uncertainty score0.175

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 head0.016
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