MétaCan
Menu
Back to cohort
Record W206890804

Seal Island Bridge Deck Replacement

2004· article· en· W206890804 on OpenAlexaboutno aff
Alan Perry, Robbie Fraser, John H G Macdonald

Bibliographic record

VenueACI Concrete International · 2004
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsDeckPrecast concreteDurabilityEngineeringStructural engineeringBridge (graph theory)Structural loadTrussDriver rehabilitationCivil engineeringComputer science
DOInot available

Abstract

fetched live from OpenAlex

The Seal Island Bridge is located on a vital stretch of the Trans-Canada Highway. Because closing the bridge to facilitate a recent rehabilitation and deck replacement project would have a significant impact on the region's economy, minimizing traffic disruption was a major factor in choosing a structural repair system. This article discusses the evaluation and construction process for the bridge project. After considering several alternatives, a precast concrete bridge deck was chosen because it met the most important criteria: durability; constructibility and ability to meet stringent construction schedules while minimizing traffic disruption; cost-efficiency in terms of both capital and life cycle costs; and contribution to the stiffness and damping of the supporting structure for vibration control. The existing steel superstructure was reinforced to carry the weight of the new structure and to meet the current design live load code. The construction sequence allowed the retention of a driving lane while replacing half of the deck. Only three overnight closures per week were required. The new deck system is lighter than a conventional cast-in-place concrete deck system, which reduced the amount of truss reinforcement required. The new deck system is also more durable than conventional systems since it is designed to be crack-free under service load 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 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.267
Threshold uncertainty score0.583

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 head0.008
GPT teacher head0.226
Teacher spread0.218 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations0
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueACI Concrete InternationalSame topicStructural Engineering and Vibration AnalysisFrench-language works237,207