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Record W1532814773

Comparison between CRLH zeroth-order antenna and series-fed microstrip patch array antenna

2009· article· en· W1532814773 on OpenAlexaff
Thorsten Liebig, Andreas Rennings, S. Otto, Christophe Caloz, Daniel Erni

Bibliographic record

VenuePolyPublie (École Polytechnique de Montréal) · 2009
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsPatch antennaMicrostrip antennaMicrostripResonatorPhysicsAntenna (radio)Leaky wave antennaOptoelectronicsElectrical engineeringOpticsEngineering
DOInot available

Abstract

fetched live from OpenAlex

A metal-insulator-metal (MIM) composite right/left-handed (CRLH) series-mode zeroth-order resonant antenna (ZORA) optimized for the 24 GHz ISM band is presented and compared to a series-fed patch array (SFPA) antenna. The CRLH ZORA exhibits superior performances for relatively short lengths (≪ 3λ 0 ) whereas the SFPA may performs better, depending on the specific design, when the length is very long (≫ 5λ 0 ), so that the resonant antennas operate as leaky-wave antennas with a leakage factor proportional to the density of the radiators along the structure. To our knowledge it the first time that the leaky-wave operation of an electrically very large “resonator” has been explicitly identified. The ZORA is particularly recommended for average electrical sizes in the order of 2λ 0 , where it should be systematically superior to a SFPA.

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 score0.002
Threshold uncertainty score0.006

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.013
GPT teacher head0.243
Teacher spread0.230 · 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

Citations9
Published2009
Admission routes1
Has abstractyes

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