MétaCan
Menu
Back to cohort
Record W1998669261 · doi:10.1121/1.4776789

Acoustics spectral gaps and transmission in periodic stub tuners

2003· article· en· W1998669261 on OpenAlexaff
M. S. Kushwaha, P. Vasilopoulos, X. F. Wang

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2003
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsConcordia University
Fundersnot available
KeywordsStub (electronics)PhysicsTransfer matrixWaveguideVibrationTransmission (telecommunications)Binary numberBand gapOpticsAcousticsCondensed matter physicsTelecommunicationsMathematicsComputer scienceElectronic engineering

Abstract

fetched live from OpenAlex

Periodic binary systems can give rise to genuine acoustic stop bands within which sound and vibrations remain forbidden. Extensive band structure and transmission are computed for a periodically stubbed waveguide. In general the waveguide segments and stubs are made of different materials. The acoustic wave in such a system has two independent polarizations: out-of-plane and in-plane modes. The band structure and transmission spectrum are studied for diverse geometries using a simple and efficient version of the transfer-matrix method [Phys. Rev. B 65, 035107 (2002)]. For the same material between the waveguide and symmetric stubs the width of some gaps can change, upon varying the stub length or width, by more than one order of magnitude. A further modulation can be achieved for different materials between the stubs and the main waveguide or if the stubs are asymmetric. The spectral gaps in the band structure of an infinitely long system correspond to those in the transmission spectrum of the same system but with a finite number n of units. For n finite (i) there exist pseudogaps that gradually turn into complete gaps with increasing n and (ii) the introduction of defects gives rise to states inside the gaps and leads to transmission resonances.

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 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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.605
Threshold uncertainty score0.232

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 head0.009
GPT teacher head0.227
Teacher spread0.218 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2003
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of the Acoustical Society of AmericaSame topicAdvanced Antenna and Metasurface TechnologiesFrench-language works237,207