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Record W2592529055 · doi:10.3390/buildings7010018

The Acoustics of the Double Elliptical Vault of the Royal Palace of Caserta (Italy)

2017· article· en· W2592529055 on OpenAlexaff
Umberto Berardi, Gino Iannace, Amelia Trematerra

Bibliographic record

VenueBuildings · 2017
Typearticle
Languageen
FieldHealth Professions
TopicNoise Effects and Management
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsVault (architecture)ProcessionScenographyFluteVisual artsEngineeringArtArt historyHistoryAncient history

Abstract

fetched live from OpenAlex

This work investigates the acoustic characteristics of the double elliptical vault, which overlooks the Grand Staircase of the Royal Palace of Caserta (Italy). The Royal Palace was built by the architect Luigi Vanvitelli in the Seventeenth Century and it is the largest royal building in Italy. The double elliptical vault presents a great scenography effect. Inside the vault, on the planking level, musicians used to play for the king and his guests when the royal procession, going up the grand staircase, entered the royal apartments, creating astonishment among the guests who heard the music without understanding from where it was coming. Since the musicians were inside the vault, the long reverberation made the listeners perceive the vault to be enveloped by the music. To investigate this effect, the acoustic characteristics of the double vault were measured, putting the sound source on the planking level of the vault, while the microphones were put along the staircase and in the vestibule towards the royal apartments. Finally, the spatial distribution of several acoustic parameters is evaluated also using architectural acoustic simulations.

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)0.001
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.837

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.034
GPT teacher head0.377
Teacher spread0.344 · 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 designObservational
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

Citations10
Published2017
Admission routes1
Has abstractyes

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