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Record W605112544 · doi:10.33593/iccp.v9i1.454

Design and Construction of a Pervious Concrete Pavement in Ontario, Canada

2025· article· en· W605112544 on OpenAlexfundaboutno aff
C Raymond, Becca Lane, Maria Bianchin, Stephen Senior, M Titherington

Bibliographic record

VenueProceedings of the International Conference on Concrete Pavements · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Stormwater Management Solutions
Canadian institutionsnot available
FundersUniversity of WaterlooCement Association of Canada
KeywordsPervious concreteSubgradeCivil engineeringGeotechnical engineeringChristian ministryEngineeringPavement engineeringEnvironmental scienceCementAsphalt

Abstract

fetched live from OpenAlex

The Ontario Ministry of Transportation (MTO) designed and constructed its first pervious concrete pavement in 2007. The pervious concrete pavement serves as a commuter parking lot located adjacent to Highway 401 near Milton, Ontario, approximately 50 km west of Toronto. The final design consists of 240 mm of pervious concrete over 100 mm of open graded clear stone, over 200 mm of granular base material, over select subgrade material, over silty sand subgrade. Pervious concrete pavements provide many environmental benefits and are deemed a stormwater management best practice. These benefits may be offset by concerns with winter durability and the potential for clogging, especially with traditional winter maintenance. The Contractor elected to use a Bid-Well bridge deck finishing machine for placing the majority of the pervious concrete pavement. A Razorback screed (i.e. air driven steel truss) was used to construct the last section of the pavement. This paper presents the design considerations and summarizes the construction observations and lessons learned. Laboratory performance data for the pervious concrete pavement are also presented.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.039
Threshold uncertainty score0.209

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.021
GPT teacher head0.216
Teacher spread0.195 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2025
Admission routes2
Has abstractyes

Explore more

Same venueProceedings of the International Conference on Concrete PavementsSame topicUrban Stormwater Management SolutionsFrench-language works237,207