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Record W2270314744

Effect of Coloring Pigment on Asphalt Mixture Performance: Case for Use in Ontario

2016· article· en· W2270314744 on OpenAlexaboutno aff
Sina Varamini, Susan Tighe

Bibliographic record

VenueTransportation Research Board 95th Annual MeetingTransportation Research Board · 2016
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsAsphaltRutAggregate (composite)Environmental scienceCrackingStiffnessAsphalt pavementForensic engineeringCivil engineeringEngineeringMaterials scienceComposite materialStructural engineering
DOInot available

Abstract

fetched live from OpenAlex

Located north of Toronto, Ontario, York Region is a thriving community which is proactive in promoting efficient transportation. To meet its rapidly increasing need for public transit, York Region has used a combination of coloured aggregate and red pigment for its dedicated Bus Rapid Transit (BRT) dedicated lanes. The intent is that the use of coloured asphalt is intended to improve level of safety through enhanced visibility. The dedicated lanes are located along the three most heavily travelled roads in the region; Yonge Street, Highway 7, and Davis Drive. The research presented in this paper relates to an on-going partnership between the Centre for Pavement and Transportation Technology (CPATT) at the University of Waterloo, York Region, and Metrolinx. This paper presents some of the background related to how coloured asphalt can be used in various transportation applications to achieve various technical and social benefits. It also highlights some of the material characterization test results for the Superpave 12.5 mm coloured asphalt surface mixtures including the dynamic modulus testing, Thermal Stress Restrained Specimen Test, and flexural fatigue testing. Plant-produced Coloured Hot Mix Asphalt (CHMA) as well as laboratory-fabricated samples are being evaluated. Overall observations suggest that pigmentation had affected the level of resistance to fatigue cracking, but large variation was observed in fatigue results that requires further investigation of testing procedure. No affect was observed in overall stiffness of the mixture at higher and lower temperatures.

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)0.009
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.240
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0090.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.064
GPT teacher head0.362
Teacher spread0.298 · 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 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

Citations1
Published2016
Admission routes1
Has abstractyes

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