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Record W3008764294 · doi:10.1109/lawp.2020.2974455

Low-Cost High-Gain Superstrate Antenna Array for 5G Applications

2020· article· en· W3008764294 on OpenAlexaff
Yazan Al-Alem, Ahmed A. Kishk

Bibliographic record

VenueIEEE Antennas and Wireless Propagation Letters · 2020
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsConcordia University
Fundersnot available
KeywordsHigh-gain antennaBandwidth (computing)Antenna gainAntenna arrayArray gainTransceiverAntenna measurementExtremely high frequencyDipole antennaReflective array antennaElectronic engineeringAntenna (radio)Computer scienceOpticsPhysicsAntenna efficiencyOptoelectronicsEngineeringTelecommunicationsSlot antennaWireless

Abstract

fetched live from OpenAlex

A high-gain superstrate antenna array is designed at 60 GHz. The proposed antenna array is extremely low in cost and possesses high performance metrics. The proposed structure can be integrated easily into many modern millimeter-wave/5G transceivers. The array boresight gain is 19.4 dBi, the relative bandwidth is 10.7%, and the maximum gain variation is 1.7 dB within the operating bandwidth.

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 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: none
Teacher disagreement score0.731
Threshold uncertainty score0.865

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 head0.016
GPT teacher head0.219
Teacher spread0.203 · 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.

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

Citations20
Published2020
Admission routes1
Has abstractyes

Explore more

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