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Record W2924173233 · doi:10.2749/vancouver.2017.0042

Innovative Expansion Joint Replacement for Burlington Bay Skyway

2017· article· en· W2924173233 on OpenAlexaffabout
Joseph Ostrowski, Sherif Sidky, David Lai

Bibliographic record

VenueReport · 2017
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsExpansion jointJoint (building)Modular designBridge (graph theory)EngineeringSeal (emblem)Service (business)RetrofittingTransport engineeringStructural engineeringComputer scienceBusiness

Abstract

fetched live from OpenAlex

The innovative expansion joint replacement design for the Burlington Bay Skyway Northbound Structure in Hamilton, Ontario resulted in substantial economic and social benefits. The existing modular expansion joints were distressed and at the end of their service lives. Joint replacement was complicated by several constraints, including high traffic volumes, limited detour options, a restriction against full closures of the bridge, a moratorium by the client agency on splicing modular joint assemblies, and the limited available load capacity of the structure. The bridge articulation was modified and the existing breather joints were mobilized to reduce movement at 16 modular expansion joints. This allowed these joints to be successfully replaced with an innovative prefabricated module expansion joint assembly incorporating a single strip seal. The design minimized traffic closures and disturbance to the public, while also realizing substantial cost savings.

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)0.000
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: Other · Consensus signal: none
Teacher disagreement score0.024
Threshold uncertainty score0.049

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0070.002

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 head0.026
GPT teacher head0.276
Teacher spread0.250 · 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
GenreOther

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
Published2017
Admission routes2
Has abstractyes

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