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Record W643844595

10 years of concrete pavement maintenance innovation to extend service life

2011· article· en· W643844595 on OpenAlexaboutno aff
David Hein

Bibliographic record

Venue24th World Road CongressWorld Road Association (PIARC) · 2011
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsPavement managementEngineeringRevenueBridge maintenanceTransport engineeringDriver rehabilitationTollExpansion jointForensic engineeringCivil engineeringBusinessRehabilitation
DOInot available

Abstract

fetched live from OpenAlex

The Highway 407 Express Toll Route (ETR) concession in Ontario, Canada is responsible for the management of a large highway network for a period of 99 years. As a part of that concession, 407 ETR manages over 600 lane-kilometres of exposed concrete highway. 407 ETR has a very active pavement maintenance and preservation program to maximize the life of the pavement. Also, as a private sector concession, they have the ability to act quickly and actively partner with industry to promote innovation. 407 ETR has a very active pavement management and maintenance management system that is used for future needs planning but more importantly is used to identify maintenance and rehabilitation needs early in their development so that they can be addressed using a less expensive preventive maintenance program. It is in the best interest of the concession to maximize the life of the pavement and to provide a very high quality riding surface for the paying public and to avoid disruptions to traffic flow and revenue. To accomplish this, 407 ETR has employed many maintenance techniques including: slab stitching, dowel bar retrofit, joint retrofit, diamond grinding, shot blasting, longitudinal grooving, underslab sealing and lifting, targeted slab replacement, micro-surfacing and other proprietary thin asphalt surfaces. This paper reviews each of the concrete pavement maintenance and repair techniques used by 407 ETR over the past 10 years, discusses their performance and provides guidance on “what to do and what not to do” aspects of their use and compares their lifecycle benefits.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
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
Bibliometrics0.0010.003
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.025
GPT teacher head0.243
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; both teacher heads agree on what is shown here.

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

Citations0
Published2011
Admission routes1
Has abstractyes

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