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Record W2747787074 · doi:10.1109/tmtt.2017.2737989

Band-Switchable Substrate-Integrated Waveguide Resonator and Filter

2017· article· en· W2747787074 on OpenAlexaff
Boyoung Lee, Beyoungyoun Koh, Seunggoo Nam, Tae‐Hak Lee, Juseop Lee

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2017
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsPolytechnique Montréal
FundersNational Research Foundation of KoreaMinistry of Science, ICT and Future Planning
KeywordsPassbandBand-pass filterResonatorWaveguide filterPrototype filterm-derived filterFilter (signal processing)Materials scienceOptoelectronicsSubstrate (aquarium)WaveguideFilter designElectronic engineeringOpticsPhysicsEngineeringElectrical engineering

Abstract

fetched live from OpenAlex

In this paper, we present a new band-switchable substrate-integrated waveguide (SIW) filter structure and its design method. The filter can have a passband either in S- or X-band, or have two passbands-one in S-band and the other one in X-band-at the same time. The presented design method allows us to obtain the bandwidths of two passbands independently. To verify the presented filter structure and design method, we have designed, fabricated, and measured three bandpass filters having three different pairs of bandwidths using frequency-tunable SIW resonators. By virtue of the frequency-tunable resonators, the filter can be continuously tuned in both frequency bands.

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: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.003

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 communication0.0000.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.010
GPT teacher head0.224
Teacher spread0.214 · 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

Citations31
Published2017
Admission routes1
Has abstractyes

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