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Record W2161768776 · doi:10.1260/135101002320815684

Modelling of Scattering from Balcony Fronts

2002· article· en· W2161768776 on OpenAlexfundno aff
Т. М. Чан, Wai Ming To

Bibliographic record

VenueBuilding Acoustics · 2002
Typearticle
Languageen
FieldNeuroscience
TopicHearing Loss and Rehabilitation
Canadian institutionsnot available
FundersNational Research Council Canada
KeywordsWavefrontScatteringRay tracing (physics)AcousticsOpera houseFront (military)Room acousticsReflection (computer programming)OperaOpticsGeologyComputer sciencePhysicsReverberationMeteorologyArtVisual arts

Abstract

fetched live from OpenAlex

Balconies are normally used in large auditoria such as concert halls or opera houses, to increase seating capacity or to give better view for a distinguished group of the audience. When ray-tracing based computer models are applied to study the acoustical quality of these auditoria, the alteration of the sound field due to balcony fronts is normally unobservable, because of the relative small size of the balcony fronts in the auditorium. Furthermore, most diffuse reflection ray-tracing methods are not based on direct wave acoustics but on an approximation of the scattering effect. In practice, experience shows that balcony fronts give additional warmth to music. This effect is more prominent when singers perform in traditional horseshoe shaped opera houses with multi-levels balconies. This paper describes modelling of scattering from balcony fronts using a theoretical wave approach, in which the incident wave front is not plane but spherical. A computer simulation illustrates the scattering of sound that takes place when the wavefront impinges on the surface of the balcony fronts.

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: Empirical
Teacher disagreement score0.607
Threshold uncertainty score0.333

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 head0.084
GPT teacher head0.269
Teacher spread0.185 · 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

Citations1
Published2002
Admission routes1
Has abstractyes

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