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Record W1964940190 · doi:10.1002/mop.21805

Equivalence between substrate‐integrated (SIRW) rectangular waveguide short‐circuit load and its equivalent rectangular waveguide short‐circuit load

2006· article· en· W1964940190 on OpenAlexaff
Wenquan Che, Lei Xu, Dapeng Wang, Liang Geng, Kuan Deng, Y.L. Chow

Bibliographic record

VenueMicrowave and Optical Technology Letters · 2006
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Waterloo
FundersNatural Science Foundation of Jiangsu ProvinceNational Natural Science Foundation of China
KeywordsPlanarEquivalence (formal languages)MicrowaveWaveguideEquivalent circuitExtremely high frequencyCylinderElectronic circuitSubstrate (aquarium)Materials scienceOpticsMathematicsEngineeringOptoelectronicsElectrical engineeringGeometryPhysicsTelecommunicationsComputer scienceVoltagePure mathematics

Abstract

fetched live from OpenAlex

Abstract Substrate integrated rectangular waveguide (SIRW) is an artificial rectangular waveguide (RW) constructed in planar substrate with two rows of periodic metallized posts or slots. In this letter, the equivalence formula between the locations of the corresponding short circuits by cylinder walls and by the solid wall was derived, based on the former width equivalence formula of the SIRW and its equivalent RW [( 11 )]]. The theoretical and simulation results are given for the SIRW short load and RW short load, good agreements have been observed. Such equivalences are convenient for the design of small waveguides, of millimeter wave, in a multilayer circuit structure, such as the LTCC etc. © 2006 Wiley Periodicals, Inc. Microwave Opt Technol Lett 48: 1694–1698, 2006; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.21805

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 score0.003
Threshold uncertainty score0.010

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 studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.216
Teacher spread0.199 · 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

Citations15
Published2006
Admission routes1
Has abstractyes

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