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Record W30524269 · doi:10.33593/iccp.v8i1.529

A Pilot Study of Instrumented Unbonded Concrete Overlay in Toronto

2025· article· en· W30524269 on OpenAlexaboutno aff
Susan Tighe, Wilson Chung, Fiona Leung, Tom Ellerbusch, Rico Fung

Bibliographic record

VenueProceedings of the International Conference on Concrete Pavements · 2025
Typearticle
Languageen
FieldEngineering
TopicInfrastructure Maintenance and Monitoring
Canadian institutionsnot available
Fundersnot available
KeywordsOverlayCivil engineeringEngineeringDriver rehabilitationTransport engineeringStructural engineeringComputer scienceRehabilitation

Abstract

fetched live from OpenAlex

Unbonded concrete overlays provide structural rehabilitation and can be cost effective when the existing pavements are highly distressed and/or removal of existing pavement layers is not desirable. This paper describes a pilot study, which involves a three way partnership between the University of Waterloo, the Cement Association of Canada and the City of Toronto, to evaluate and document the performance of the first instrumented unbonded concrete overlay in Canada. The rehabilitation area is located at a heavily-trafficked intersection on Bloor Street and Aukland Road in the City of Toronto. The large volumes of bus traffic from the nearby subway station caused significant damage to the pavement structure. The rehabilitation design was composed of placing an unbonded concrete overlay on Bloor Street and replacing the section on Aukland Road with full depth exposed concrete. Twelve strain gauges are embedded in the concrete layer and they are strategically located along the wheel paths of the buses. The sensors are being monitored to assess long-term performance of the concrete overlay and the full depth concrete subjected to traffic and climatic loads. This paper outlines the design parameters, site conditions, and material properties of the overlay. The construction and full-scale instrumentation of this project are described, followed by preliminary analyses of up-to-date performance records.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.090
Threshold uncertainty score0.539

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 science0.0010.000
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 head0.019
GPT teacher head0.268
Teacher spread0.248 · 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 designBench or experimental
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

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueProceedings of the International Conference on Concrete PavementsSame topicInfrastructure Maintenance and MonitoringFrench-language works237,207