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Record W4381057238 · doi:10.3397/nc_2023_0047

Review and Analysis of the Vibration Assessment Procedures Advocated by the Railway Association of Canada

2023· article· en· W4381057238 on OpenAlexaffabout
Todd Busch, Carlos Yoong

Bibliographic record

VenueNOISE-CON proceedings · 2023
Typearticle
Languageen
FieldEngineering
TopicRailway Engineering and Dynamics
Canadian institutionsSoft dB (Canada)
Fundersnot available
KeywordsTrainVibrationParametric statisticsComputer scienceEngineeringAcousticsMathematicsGeographyStatisticsPhysics

Abstract

fetched live from OpenAlex

In the absence of government regulations, the Federation of Canadian Municipalities (FCM) and the Railway Association of Canada (RAC) espouse criteria for the assessment of vibration due to passing trains. Given that many municipalities follow these guidelines when considering the permitting of residential development, the effectiveness of the RAC vibration assessment methods are worth investigating. These include a limit of 0.14 mm/s RMS on amplitudes and a 75 m screening distance for triggering a detailed study of the impacts of railway vibration on developments in proximity to tracks. This paper provides a review of the criteria for their reasonableness at avoiding unwanted and/or undesirable vibration conditions for residential developments. This is accomplished through reference to the generic vibration propagation curves within the latest US Federal Railway/Transit Administrations noise and vibration guidelines and alternative parametric equations for estimating vibration propagation.

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)0.004
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.974
Threshold uncertainty score0.401

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0200.023
Science and technology studies0.0020.002
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.004
GPT teacher head0.203
Teacher spread0.199 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2023
Admission routes2
Has abstractyes

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