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Record W1963851898 · doi:10.1109/tmtt.2008.925571

MEMS-Switchable Coupled Resonator Microwave Bandpass Filters

2008· article· en· W1963851898 on OpenAlexafffund
Cen Ong, M. Okoniewski

Bibliographic record

VenueIEEE Transactions on Microwave Theory and Techniques · 2008
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsAcceleware (Canada)University of Calgary
FundersNational Institute of Standards and TechnologyCMC Microsystems
KeywordsBand-pass filterInsertion lossCapacitive sensingResonatorMicrowaveMaterials scienceCantileverMicroelectromechanical systemsOptoelectronicsFilter (signal processing)Electrical engineeringPrototype filterElectronic engineeringEngineeringLow-pass filterTelecommunications

Abstract

fetched live from OpenAlex

Two microelectromechanical systems switchable microwave bandpass filters are presented. Both filters are compact fourth-order symmetrically coupled filters-the first is designed with bridge capacitive switches, while the second uses cantilever capacitive switches. The bridge-switched filter tunes from 21.6 to 16.85 GHz with insertion losses of 0.9 and 1.0 dB, respectively. The cantilever-switched filter tunes from 21.85 to 15.15 GHz and has insertion losses of 0.6 and 1.0 dB, respectively. Both the bridge and cantilever capacitive switches are electrostatically actuated using dc voltages of 70 and 55 V, applied through high-resistivity chrome-silicide lines. The reported filters show state-of-the-art performance in insertion loss and frequency tuning characteristics.

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 score0.002
Threshold uncertainty score0.006

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)0.0020.001

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 head0.010
GPT teacher head0.205
Teacher spread0.195 · 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

Citations4
Published2008
Admission routes2
Has abstractyes

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