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Record W2892313318 · doi:10.1109/tap.2018.2870426

A Semianalytical Approach to Designing High-Transparency Low-Profile Circular Polarizers

2018· article· en· W2892313318 on OpenAlexfundno aff
Mehdi Hosseini, Sean V. Hum

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2018
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDielectricPolarizerCompact spaceComputer scienceSpace (punctuation)Transparency (behavior)Topology (electrical circuits)PhysicsMathematicsMathematical analysisOpticsCombinatoricsOptoelectronics

Abstract

fetched live from OpenAlex

This paper presents a semianalytical approach to streamline the design process of a linear-to-circular polarizer (LCP). The LCP is composed of only two identical frequency selective surfaces (FSSs) and can be based in free space or on low dielectric constant substrates. The adopted unit cell is electrically small and utilizes a modified Jerusalem cross (MJC) FSS grid. The low profile (0.11λ0) and compactness of the cells (0.17λ0× 0.17λ0) enhance the accuracy of the circuit-driven design approach and eases calculations associated with numerical simulations. When based in free space, the LCP offers axial ratios of less than 3 and 1 dB over 10% and 3.8% fractional bandwidths, with low insertion losses of 0.5 and 0.35 dB, respectively, making it appealing to both terrestrial and satellite applications.

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)0.001
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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.016
GPT teacher head0.224
Teacher spread0.209 · 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 designSimulation or modeling
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

Citations21
Published2018
Admission routes1
Has abstractyes

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