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Record W1844286089

ALBERTA'S 6 BEST BRIDGE PRACTICES

2005· article· en· W1844286089 on OpenAlexaboutno aff
R W Stidger

Bibliographic record

VenueBetter roads · 2005
Typearticle
Languageen
FieldEngineering
TopicInfrastructure Maintenance and Monitoring
Canadian institutionsnot available
Fundersnot available
KeywordsCulvertAbutmentBridge (graph theory)Best practiceEngineeringGuidelineBridge deckFoundation (evidence)UnderpinningForensic engineeringConstruction engineeringCivil engineeringDeckStructural engineering
DOInot available

Abstract

fetched live from OpenAlex

This article describes best practice bridge maintenance guidelines prepared by the Alberta Department of Transportation for assessments, corrosion control, design, deck rehab, abutments, and footings. Assessments determine the best long-term solution, resulting in maintenance, rehabilitation, or replacement. Factors affecting assessment include condition deficiencies, functional deficiencies, and proposed highway improvements. Corrosion control is achieved through the use of metal culverts. Alternate design is used as a best practice guideline when a bridge is past repair and replacement is the next step. Alternate designs involve an estimated cost difference which is factored according to product development, schedules, cost trends, and aesthetics. Concrete bridge deck rehab is another best practice guideline. Measures that may be selected are based on life-cycle costs. Integral abutments, which are best used on short bridges, aid in eliminating abutment joints and reducing maintenance. Spread footing foundation designs are the last best practice guidelines discussed. While they may be viable alternatives for grade separations, abutments, and land-based piers, their usage may not always be appropriate due to inspection and potential underpinning needs.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.722
Threshold uncertainty score0.637

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)0.0000.000

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 head0.013
GPT teacher head0.248
Teacher spread0.235 · 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 designNot applicable
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
Published2005
Admission routes1
Has abstractyes

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