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Record W2094139026 · doi:10.1139/t00-117

Complex permittivity measurement system for detecting soil contamination

2001· article· en· W2094139026 on OpenAlexfundvenueno aff
R. Kerry Rowe, Julie Q. Shang, Y Xie

Bibliographic record

VenueCanadian Geotechnical Journal · 2001
Typearticle
Languageen
FieldEnvironmental Science
TopicSoil Moisture and Remote Sensing
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPermittivityContaminationSoil waterDielectric permittivityDielectricRelative permittivitySoil testEnvironmental scienceGeotechnical engineeringSoil scienceMaterials scienceGeologyOptoelectronics

Abstract

fetched live from OpenAlex

The design, calibration, and operation of a laboratory-scale system to assess the viability of detecting contaminants in soil based on changes in its electromagnetic response are described. The complex permittivity measurement device, permeation apparatus, and dielectric responses of soil specimens measured before and after permeation with different CaCl 2 solutions are discussed. It is shown that the change in the complex permittivity of the soil is best characterized in terms of the permittivity and loss factor at the frequency of 250 MHz, since they exhibit a significant response to changes in the pore-fluid chemistry. The laboratory system can be used routinely to create soil samples permeated with a known contaminant at known concentrations and then measure the complex permittivity of the contaminated soil samples directly after permeation. The system is such that other factors (e.g., density and water content) which could influence the complex permittivity can be carefully controlled, allowing the relationship between the type and level of contamination and dielectric behaviour of soils to be established.Key words: complex permittivity, nondestructive testing, soil contamination, detection of soil contamination, environmental technology.

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)0.001
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: Empirical
Teacher disagreement score0.949
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
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 head0.035
GPT teacher head0.231
Teacher spread0.196 · 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 designOther design
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

Citations32
Published2001
Admission routes2
Has abstractyes

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