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Record W2332898054 · doi:10.1515/htmp-2012-0158

Temperature Dependencies of the Permittivities and Microwave Shielding Effectiveness of a Carbon-containing Electrically Conductive Concrete

2013· article· en· W2332898054 on OpenAlexaff
Brandon Chambers, C.A. Pickles, Peter J. Tumidajski

Bibliographic record

VenueHigh Temperature Materials and Processes · 2013
Typearticle
Languageen
FieldMaterials Science
TopicElectromagnetic wave absorption materials
Canadian institutionsSt. Clair CollegeQueen's University
Fundersnot available
KeywordsElectromagnetic shieldingElectrical conductorMaterials scienceMicrowaveComposite materialShielding effectElectrically conductivePermittivityDielectricOptoelectronicsComputer scienceTelecommunications

Abstract

fetched live from OpenAlex

Abstract Conductive concrete is a construction material that can be utilized for a number of applications: in particular, electromagnetic shielding. In this research, the microwave shielding effectiveness of a carbon containing electrically conductive concrete was determined from both the real and the imaginary permittivities. Also, the permittivities and the shielding effectiveness of a normal concrete were determined for comparison purposes. It was shown that the permittivities of the conductive concrete were significantly higher than those of the normal concrete. The shielding abilities of both of the concretes were determined as a function of concrete thickness and temperature, and the conductive concrete had a superior shielding effectiveness. For the normal concrete, at room temperature and a frequency of 912 MHz, a shielding effectiveness of 30 dB was achieved for a thickness of about 400 cm. For the conductive concrete, under the same conditions, a thickness of only about 3 cm was required to achieve the same shielding effectiveness.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.005
GPT teacher head0.197
Teacher spread0.191 · 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

Citations4
Published2013
Admission routes1
Has abstractyes

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