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Record W2483605593 · doi:10.1002/mop.30037

Wideband bandpass filter with high selectivity based on dual‐mode DGS resonator

2016· article· en· W2483605593 on OpenAlexaff
Biao Peng, Shufang Li, Jianfeng Zhu, Qianyun Zhang, Li Deng, Qingsheng Zeng, Yue Gao

Bibliographic record

VenueMicrowave and Optical Technology Letters · 2016
Typearticle
Languageen
FieldEngineering
TopicMicrowave Engineering and Waveguides
Canadian institutionsUniversity of Ottawa
FundersNational Natural Science Foundation of China
KeywordsStopbandPassbandWidebandResonatorBand-pass filterInsertion lossBandwidth (computing)MicrowaveAttenuationPhysicsMaterials scienceDual modeAcousticsOptoelectronicsElectronic engineeringOpticsEngineeringTelecommunications

Abstract

fetched live from OpenAlex

Abstract A wideband bandpass filter based on dual‐mode defected ground structure resonator (DGSR) is designed and effectively analysed by utilising the even‐/odd‐mode theory and equivalent circuit models. The lower and upper cutoff frequencies of the filter can be independently tuned by adjusing the even‐ and odd‐mode resonant frequencies of the dual‐mode DGSR, respectively. The fabricated prototype is centred at 2.27 GHz with a wide bandwidth (FBW 63.4%), low insertion loss (0.386 dB), high selectivity and wide stopband. The attenuation slopes in the lower and upper passband transitions are 108.5 and 136.9 dB/GHz, respectively. The stopband rejection is better than 22 dB up to 6 GHz (2.6 f0). © 2016 Wiley Periodicals, Inc. Microwave Opt Technol Lett 58:2300–2303, 2016

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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
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)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.004
GPT teacher head0.177
Teacher spread0.173 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations9
Published2016
Admission routes1
Has abstractyes

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