MétaCan
Menu
Back to cohort
Record W562160055

FRP Bridge Evolution

2007· article· en· W562160055 on OpenAlexvenueno aff
Jim Williams

Bibliographic record

VenueBridges Conversations in Global Politics and Public Policy · 2007
Typearticle
Languageen
FieldEngineering
TopicStructural Behavior of Reinforced Concrete
Canadian institutionsnot available
Fundersnot available
KeywordsFibre-reinforced plasticBridge (graph theory)Bridge deckDeckBeam (structure)Load testingSoftware deploymentAcceptance testingEngineeringStructural engineering
DOInot available

Abstract

fetched live from OpenAlex

The Texas Department of Transportation has expanded its research implementation of custom fiber-reinforced polymer (FRP) composite bridge beams for a new drainage ditch bridge in Refugio County, Texas. Beginning in late 2006 and scheduled for completion in summer 2007, the project's goal was to take the lessons learned from a previous hybrid bridge project and evolve the current customization and production processes in hopes of optimizing performance and cost variables for future projects. This article describes the construction of this project, which uses customized FRP, flanged U-shaped beams and a concrete deck construction. The beams were fabricated using a vacuum infusion process to optimize the physical properties of the beam and facilitate production. Prior to installation, an acoustic emission evaluation test on two beams was conducted. The tests monitored emission during the background check prior to loading, during load holds, and during the background check after completion of loading. The test verified the performance of the beams under the load criteria set forth by the project specifications. The beams each weigh approximately 5,000 lb and sit on abutments where the concrete deck poured onto them. The lightweight FRP beams allowed for easy delivery and rapid onsite deployment. A post-construction assessment indicated that the beams are actually stronger than anticipated.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.931
Threshold uncertainty score0.999

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 head0.015
GPT teacher head0.264
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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueBridges Conversations in Global Politics and Public PolicySame topicStructural Behavior of Reinforced ConcreteFrench-language works237,207