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Record W2897512819 · doi:10.1121/1.5067840

Noise and vibration measurements of a machine-room-less elevator system

2018· article· en· W2897512819 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.

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2018
Typearticle
Languageen
FieldEngineering
TopicElevator Systems and Control
Canadian institutionsRowan Williams Davies & Irwin (Canada)
Fundersnot available
KeywordsElevatorHoist (device)VibrationVibration isolationAutomotive engineeringNoise (video)Computer scienceStructural engineeringEngineeringAcousticsPhysicsArtificial intelligence

Abstract

fetched live from OpenAlex

A trend in the design of new condominium buildings is the use of “machine-room less” (MRL) elevator systems. The primary difference between MRL elevator systems and more traditional elevator systems is that, rather than locating the hoist machinery in a rooftop penthouse, the hoist machinery is installed in the elevator shaft. In this location (which is typically closer to residential units), there is greater potential for the operation of the machinery to result in complaints from residents of excessive noise and vibration levels. This paper presents a case study of noise and vibration measurements that were conducted in a condominium building with a MRL elevator system. Measurements were conducted both within the affected residential unit as well as in the elevator shaft. In conducting the measurements, particular attention was paid to determining the effectiveness of the vibration isolation that was provided for the elevator hoist machinery within the elevator shaft.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.942
Threshold uncertainty score0.215

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 studies0.0000.000
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 head0.011
GPT teacher head0.213
Teacher spread0.201 · 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