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Record W3128980219 · doi:10.2749/vancouver.2017.3150

Innovative Design and Construction of Special Guideway Structures for Vancouver’s New Evergreen Line SkyTrain Extension

2017· article· en· W3128980219 on OpenAlexaffabout
Sean O’Hagan, Monica Galloway Burke, Jianping Jiang

Bibliographic record

VenueReport · 2017
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Analysis
Canadian institutionsWSP (Canada)
Fundersnot available
KeywordsPrecast concreteScope (computer science)Transport engineeringEngineeringCivil engineeringLine (geometry)Railway lineLight railRail transitTelecommunicationsArchitectural engineeringComputer sciencePublic transportMathematicsGeometry

Abstract

fetched live from OpenAlex

The new Evergreen Line is an 11 kilometre extension to the existing SkyTrain advanced light rail transit system in Metro Vancouver, British Columbia, Canada. The project scope includes design and construction of six new stations, expansion of one existing station, nine kilometres of elevated and at-grade guideway, and a two-kilometre bored tunnel. This paper focuses on innovative design of the elevated guideway “Special Structures” where the standard precast segmental construction was not suitable. The necessity of constructing Special Structures is primarily driven by the complexity of the guideway and station geometry, and constraints imposed by properties, municipal infrastructure, railway tracks, and by connecting to an existing station. Construction challenges included working in constrained linear corridors, through multiple municipal jurisdictions, and over private properties and active railway lines.

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 score0.948
Threshold uncertainty score0.104

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.025
GPT teacher head0.262
Teacher spread0.237 · 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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