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Record W3134316278 · doi:10.2749/newyork.2019.2638

Objective-based equivalent static wind loads for long-span bridges

2019· article· en· W3134316278 on OpenAlex
Zachary J. Taylor, Pierre-Olivier Dallaire, Stoyan Stoyanoff

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

VenueReport · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicWind and Air Flow Studies
Canadian institutionsRowan Williams Davies & Irwin (Canada)
Fundersnot available
KeywordsAeroelasticityStructural engineeringTime domainModalDeflection (physics)Wind engineeringSpan (engineering)Frequency domainModal analysisDesign processComputer scienceEngineeringAerodynamicsFinite element methodAerospace engineeringPhysicsMaterials science

Abstract

fetched live from OpenAlex

<p>The process to arrive at design wind loads for long-span bridges involves experimental testing and analytical methods. Time domain simulations are becoming increasingly common and many available studies demonstrate results of buffeting response analysis in the time domain. However, there is significantly more to the process than the response analysis to derive wind loads that can be applied practically for design. The current study focuses on two key aspects required to derive design wind loads: prediction of the peak modal deflection and derivation of modal combination coefficients using objective functions.</p>

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.018
Threshold uncertainty score0.741

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)0.0010.000

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 head0.015
GPT teacher head0.259
Teacher spread0.244 · 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