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Record W2481663233

Dynamic analysis of a pedestrian walkway, University of British Columbia, Canada

2002· article· en· W2481663233 on OpenAlexaboutno aff
Carlos E. Ventura, Mehdi Kharrazi, Martin Turek, T. Horyna

Bibliographic record

VenueConference on structural dynamics · 2002
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsBridge (graph theory)PedestrianEngineeringVibrationStructural engineeringCivil engineeringAcoustics
DOInot available

Abstract

fetched live from OpenAlex

This paper presents a two-part study examining the effect of age, and the effect of temperature on a pedestrian walkway. Two sets of ambient vibration tests were performed on the walkway at the Civil and Mechanical Engineering building, UBC, one in 1994 and the other in 2001. Each time the tests were performed to determine its mode shapes and natural frequencies. The testing done in 1994 utilized the Hybrid Bridge Evaluation System developed at UBC. This test captured the first twelve vibration modes of the bridge. The tests performed in 2001 used a similar data acquisition system, as well as similar test setups, but applied new, more sophisticated software to analyse the data. The 2001 experimental program included two different tests. The first was performed on a day having normal weather conditions, intended to compare the 1994 and 2001 results, investigating any changes in the dynamic properties over seven years of use. The results were compared using the 1994 results. The second test was performed on a day with significantly higher temperatures, with the intent of investigating the effect of temperature on the behaviour of the bridge, as well as the performance of the experimental methods during those conditions.

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)0.000
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.953
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0050.001

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 head0.007
GPT teacher head0.170
Teacher spread0.162 · 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 designObservational
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

Citations2
Published2002
Admission routes1
Has abstractyes

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