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Record W2780647042

Noise Isolation Class (NIC) Testing of Modular Office Partitions

2017· article· en· W2780647042 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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueCanadian acoustics · 2017
Typearticle
Languageen
FieldEngineering
TopicGeophysical Methods and Applications
Canadian institutionsRowan Williams Davies & Irwin (Canada)
Fundersnot available
KeywordsPlenum spaceCeiling (cloud)Modular designDebuggingTileComputer scienceUndoingEngineeringStructural engineeringAcousticsArchitectural engineeringMechanical engineeringOperating system
DOInot available

Abstract

fetched live from OpenAlex

A trend in the design of new office spaces, and the renovation of existing office spaces, is to use modular partitions that terminate at suspended acoustic tile (T-bar) ceilings. These partitions permit office spaces to be reconfigured in the future with less effort than would be required with conventional gypsum wall board (GWB) partitions. Modular partitions, however, present challenges in terms of providing adequate acoustical privacy as they must be sealed around their perimeter joints and there is also potential for sound to travel over the partitions via the ceiling plenum. While the ceiling plenum transmission can be addressed by selecting ceiling tiles with an appropriate Ceiling Attenuation Class, and/or by inserting barrier elements into the plenum space, providing effective seals at the perimeter joints can be more challenging. Furthermore, modular partitions that demise offices from corridors or open-plan work areas, also require effective seals along the perimeters and bottoms of doors. This paper presents case-studies which highlight the challenges involved in providing acoustical privacy when using modular partitions.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.681

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 head0.032
GPT teacher head0.250
Teacher spread0.219 · 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