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Record W7160919665 · doi:10.1121/10.0040570

Groundborne vibration isolation of a recycling depot to protect sensitive laboratory equipment

2025· article· en· W7160919665 on OpenAlexaff
Brian Howe, Wilson Byrick

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2025
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsBGC Engineering (Canada)
Fundersnot available
KeywordsVibration isolationVibrationTruckShakerIsolation (microbiology)Transmission (telecommunications)

Abstract

fetched live from OpenAlex

A post-secondary institution conducting medical research was operating a nuclear magnetic resonance (NMR) spectrometer installed on grade in an early-20th-century building, located immediately adjacent to the university’s recycling depot. Groundborne vibration generated by trucks dropping large recycling containers onto the concrete surface caused periodic disruptions to the imaging research. To enable uninterrupted operation of the NMR, a fourfold reduction in vibration amplitude was required at a critical frequency of 16 Hz. To address this, a novel vibration isolation platform was developed to support the recycling containers and mitigate vibration transmission associated with their movement and placement. This paper presents the field vibration data collected from the mock-up phase through to final implementation, outlines the design concepts behind the platform, and shares key lessons learned during the process.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.006
GPT teacher head0.229
Teacher spread0.223 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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
Published2025
Admission routes1
Has abstractyes

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Same venueThe Journal of the Acoustical Society of AmericaSame topicStructural Engineering and Vibration AnalysisFrench-language works237,207