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Record W4251645412 · doi:10.1002/mmce.20338

Composite corporate traveling-wave power dividers for slot array waveguide antennas

2008· article· en· W4251645412 on OpenAlexafffund
Dominic Deslandes, François Boone, Ke Wu

Bibliographic record

VenueInternational Journal of RF and Microwave Computer-Aided Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversité de SherbrookePolytechnique MontréalUniversité du Québec à Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsPower dividers and directional couplersSplitterInsertion lossBandwidth (computing)MicrowavePower (physics)MicrostripElectrical engineeringWilkinson power dividerElectronic engineeringEngineeringTopology (electrical circuits)Antenna (radio)AcousticsComputer scienceFrequency dividerTelecommunicationsPhysicsOptics

Abstract

fetched live from OpenAlex

A composite corporate traveling-wave power divider is presented. The single-layer structure is composed of three parts: two interdigital traveling-wave subsections combined with a power splitter. An iterative design technique is described in which the divider is split into a number of basic blocks. Large-scaled networks are then easily designed because the whole structure does not need to be simulated. A method to take into account the insertion losses is also proposed and bandwidth enhancement is discussed, which is done by increasing the number of corporate layers. Experimental results are also shown for a 1:4 subsection. It provides equal output power with 0.5 dB of insertion loss. The phase-shift between output ports is close to the specifications of −150° at 30 GHz, with an error of less than 2°. It is also shown that this topology is well suited for frequency scanning antenna. © 2008 Wiley Periodicals, Inc. Int J RF and Microwave CAE, 2009.

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)0.000
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: none
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 communication0.0010.001
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 head0.022
GPT teacher head0.205
Teacher spread0.183 · 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

Citations2
Published2008
Admission routes2
Has abstractyes

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