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Record W2139812101 · doi:10.1142/s0218126615500188

Design of Bulk Acoustic Wave Filters for Beidou Receiver

2014· article· en· W2139812101 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Circuits Systems and Computers · 2014
Typearticle
Languageen
FieldEngineering
TopicAcoustic Wave Resonator Technologies
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsResonatorMaterials scienceAcousticsInsertion lossPiezoelectricityFilter (signal processing)Electrical impedanceElectronic filterNitrideOptoelectronicsElectronic engineeringLayer (electronics)Electrical engineeringPhysicsEngineering

Abstract

fetched live from OpenAlex

Based on the thin-film bulk acoustic resonator (FBAR) technology, a new narrow-band bulk acoustic wave (BAW) filter for Beidou B1 band receiver is designed. The aluminum nitride thin film is used as a piezoelectric layer. The Mason model of air-gap TFBAR (AGR) resonators is established in advanced design system to investigate the relationship between electrical impedance and physical parameters. The simulation results illustrate the effect of the area of parallel unit and the number of resonators on the performance of the BAW filters. By changing the series-parallel unit series and area ratio, the pass band of the BAW filter can reach 1556–1566 MHz, and the out-of-band rejection and the insertion loss can reach 47.5 dB and 3.0 dB, respectively.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.958
Threshold uncertainty score0.446

Codex and Gemma teacher scores by category

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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.021
GPT teacher head0.202
Teacher spread0.181 · 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