MétaCan
Menu
Back to cohort
Record W643576559

Falling Weight Deflectometer and Life Cycle Cost Analysis of a Major Urban Arterial Roadway Rehabilitated Using a Foamed Asphalt Stabilized Base

2012· article· en· W643576559 on OpenAlexaboutno aff
C Babuin, B Palsat, Edward Clark, K Terness

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsFalling weight deflectometerLand reclamationAsphaltLife-cycle cost analysisEngineeringCivil engineeringEnvironmental scienceTransport engineeringForensic engineering
DOInot available

Abstract

fetched live from OpenAlex

Marine Way in Burnaby, British Columbia is a major commuting route in Greater Vancouver. The roadway is currently subjected to Annual Average Daily Traffic (AADT) over 20,000 vehicles. As such, there was emphasis for construction activities to minimize delays to the travelling public. The Falling Weight Deflectometer (FWD) was used extensively in the design, construction, and post-construction phases of the project. A Life Cycle Cost Analysis (LCCA) suggested that the use of reclamation and base stabilization would provide significant savings from the alternate options. The rehabilitation strategy considered not only the long term road rehabilitation solutions but also environmental impacts and delays to the traveling public. The road was reconstructed in 2011 utilizing full depth reclamation with a Foamed asphalt Stabilized Base (FSB). During the construction phase of this project, the FWD was used to test the various stages of the foamed asphalt process, particularly at the top of the FSB surface, and at the completed asphalt surface. This data was used to verify the AASHTO design layer coefficient of the FSB layer. This case study documents the rehabilitation option selection process, construction impact mitigation measures and provides the economic justification for proceeding with the selected rehabilitation method. (A)

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.828
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.026
GPT teacher head0.275
Teacher spread0.249 · 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.

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

Citations1
Published2012
Admission routes1
Has abstractyes

Explore more

Same topicAsphalt Pavement Performance EvaluationFrench-language works237,207