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Record W2006300127 · doi:10.4133/jeeg9.4.191

Permittivity Measurements of High Conductivity Specimens using an Open-Ended Coaxial Probe—Measurement Limitations

2004· article· en· W2006300127 on OpenAlexaff
Katherine Klein

Bibliographic record

VenueJournal of Environmental and Engineering Geophysics · 2004
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsConductivityPermittivityPolarization (electrochemistry)Materials scienceElectrical resistivity and conductivityCoaxialDielectricAdmittanceElectrodeElectrical impedanceAnalytical Chemistry (journal)OpticsMineralogyPhysicsChemistryElectrical engineeringOptoelectronics

Abstract

fetched live from OpenAlex

Non-destructive electromagnetic wave-based techniques have been used for over a century to gain insight into the behaviour of geomaterials. The technique used in this study is a high frequency (20MHzto1.3GHz) open-ended coaxial probe measurement system. This study highlights the importance of knowing the limitations of the measurement system. The specimens that are tested are aqueous solutions of NaCl, CaCl2, and FeCl3 with conductivities ranging from approximately 10−3to8S∕m. Real permittivity data of the high conductivity specimens show a relaxation phenomena at MHz frequencies where none exists, indicating that electrode polarization is occurring. The frequency at which electrode polarization begins to manifest (e.g., limiting frequency) increases as the specimen conductivity increases. An empirical relationship between the limiting frequency and specimen conductivity is presented and is applied to three kaolinite-NaCl slurries. Additional problems associated with measuring high conductivity specimens using this equipment may arise since the model for the aperture admittance was optimized using low conductivity materials. Previous studies have shown that measurement errors at low frequencies are reduced if the system is calibrated using a material of similar electrical properties to the test specimen.

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)0.003
metaresearch head score (Gemma)0.013
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.013
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.094
GPT teacher head0.250
Teacher spread0.155 · 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 designBench or experimental
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

Citations8
Published2004
Admission routes1
Has abstractyes

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