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Record W2481786000 · doi:10.1061/9780784480076.012

Maximising the Use of Rubber from End-of-Life Tyres in Road Construction in Queensland

2016· article· en· W2481786000 on OpenAlexaff
Jeffrey Lee, Erik Denneman, Young Shik Choi, Christopher M. Raymond

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsMinistry of Transportation of Ontario
FundersDepartment of Transport and Main Roads, Queensland GovernmentCalifornia Department of Transportation
KeywordsAsphaltNatural rubberCrumb rubberDurabilityContext (archaeology)Fatigue crackingCrackingFiller (materials)Environmental scienceEngineeringForensic engineeringCivil engineeringMaterials scienceComposite materialGeology

Abstract

fetched live from OpenAlex

The aim of this paper is to present the potential for increasing the use of bitumen modified with ground tyre rubber in road construction and discuss the benefits of doing so. The paper seeks to identify any barriers to the increased use of the crumb rubber modified (CRM) binder within the context of Queensland, Australia. Application of ground tyre rubber in asphalt and sprayed seals provides a high value application of recycled material. The available body of knowledge shows that the use of CRM binder in both asphalt and sprayed seals can lead to improved field performance, specifically in terms of durability and cracking resistance. Significant environmental benefits may also be achieved in the form of reduced road noise, reduced CO2 emissions, and reduced use of non-renewable road construction materials. Laboratory and field testing were conducted as part of this project.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
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 head0.049
GPT teacher head0.246
Teacher spread0.198 · 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
Published2016
Admission routes1
Has abstractyes

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