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Record W1978232209 · doi:10.1049/ip-map:20040264

Low-cost free-space measurement of dielectric constant at Ka band

2004· article· en· W1978232209 on OpenAlexafffund
N. Gagnon, J. Shaker, Langis Roy, A. Petosa, Pierre Berini

Bibliographic record

VenueIEE Proceedings - Microwaves Antennas and Propagation · 2004
Typearticle
Languageen
FieldEngineering
TopicMicrowave and Dielectric Measurement Techniques
Canadian institutionsUniversity of OttawaCarleton UniversityCommunications Research Centre Canada
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDielectricCalibrationSmoothingMicrowaveSystem of measurementTransmission coefficientReflection (computer programming)Reflection coefficientConstant (computer programming)OpticsMaterials scienceTransmission (telecommunications)Electronic engineeringComputational physicsMathematicsComputer sciencePhysicsOptoelectronicsEngineeringTelecommunicationsStatistics

Abstract

fetched live from OpenAlex

A detailed method for determining the dielectric constant of materials using a Ka-band free-space transmission/reflection measurement system is presented. Since the measurement system was designed to minimise the overall cost of the system, correction terms and a smoothing process were necessary to account for limitations in the hardware. The different steps involved in the determination process are explained and their effect on the S-parameters is presented. A through-reflect-match (TRM) free-space calibration method was used, which greatly reduces system errors owing to its simple and stationary nature. The dynamic range of the measurement system after TRM calibration appeared to be better than 50 dB for the reflection coefficient and 29 dB for the transmission coefficient. To determine the unknown dielectric constant of the material, two numerical extraction techniques, a root-finding algorithm and a genetic algorithm were used. Dielectric constant results for a commercially available microwave substrate material sample are presented for both extraction techniques. The difference between the two extraction techniques was <1%. Comparison of the dielectric constant value with measurement performed by a standards testing organisation revealed an agreement within 2%.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.037
Threshold uncertainty score1.000

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 head0.014
GPT teacher head0.199
Teacher spread0.185 · 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.

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

Citations30
Published2004
Admission routes2
Has abstractyes

Explore more

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