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Record W4312323698 · doi:10.1201/9781003322641-239

Maintenance plan and durability design for the new Samuel De Champlain Bridge

2022· book-chapter· en· W4312323698 on OpenAlexaboutno aff
M. Nader, ChoongIk Choi, Nhan Vo, A. Sanjines

Bibliographic record

VenueBridge Safety, Maintenance, Management, Life-Cycle, Resilience and Sustainability · 2022
Typebook-chapter
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsDurabilityBridge (graph theory)Plan (archaeology)Forensic engineeringEngineeringHistoryComputer scienceArchaeologyMedicineDatabase

Abstract

fetched live from OpenAlex

Opened in 2019, the new Samuel De Champlain Bridge in Montreal, Canada is one of the busiest bridges in North America. The 3.4-km long-span bridge across the St. Lawrence River is comprised of three structures: A 529 m signature span featuring an asymmetric Cable-Stayed Bridge, a 762 m East Approach, and a 2044 m West Approach. Due to its geographical location, this lifeline structure faces unique engineering design challenges including extreme cold temperatures, ice abrasion, de-icing salt attacks, wind, vessel collision, scour, and seismic hazards, while meeting its design life of 125 years. A comprehensive durability plan as well as access and maintenance plans were developed by the design-build team to address material selections, the corrosion protection system, construction quality and inspection, element replacement intervals, and maintenance equipment, including the under-bridge maintenance gantry (UBMG) and electronic superstructure shuttle/ vehicle as keys to the longevity of the bridge.

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: Other
Teacher disagreement score0.989
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 studies0.0000.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0150.003

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 head0.013
GPT teacher head0.230
Teacher spread0.216 · 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
Published2022
Admission routes1
Has abstractyes

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