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Record W1937935006

Environmental noise and vibration control of the Rose Theatre, Brampton, Ontario

2010· article· en· W1937935006 on OpenAlexvenueaboutno aff
John C. Swallow, Mihkel Toome, Pearlie Yung

Bibliographic record

VenueCanadian acoustics · 2010
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsVibrationStructural engineeringRoofElevatorEngineeringVibration controlSlabNoise (video)Noise controlVibration isolationSoundproofingCivil engineeringAcousticsComputer scienceNoise reduction
DOInot available

Abstract

fetched live from OpenAlex

The Rose Theatre in Brampton, Ontario was to be constructed twenty meters away from a CN main railway line (which includes commuter and freight rail traffic) and on top of a pre-existing underground parking garage which was to remain intact and in operation during the course of construction. A full concrete slab could not be supported by the pre-existing parking garage columns; therefore, a transfer grid, designed by the structural engineer, was employed and as a result a typical room-within-a-room construction could not be conventionally achieved. Railway airborne noise is controlled to meet the interior objective of RC 20 by providing a floating shell enveloping the entire building. Exterior concrete pre-cast panels are resiliently supported and resiliently connected back to the building and the entire roof slab was vibration isolated from the structure. For railway-induced vibration, the building was supported on a transfer grid which was in turn supported by 250 mm thick rubber vibration isolation pads. The entire building, including exterior shell, stairs and elevators is vibration isolated from ground-borne rail vibration. The measured vibration levels (and the noise radiated by vibrating surfaces) in the theatre were controlled to well within the design objective.

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 score0.655
Threshold uncertainty score0.986

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 head0.002
GPT teacher head0.140
Teacher spread0.138 · 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
Published2010
Admission routes2
Has abstractyes

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