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Record W1568044936

Australian Application of International Developments in Stone Mastic Asphalt (SMA)

2006· article· en· W1568044936 on OpenAlexaboutno aff
Rob Vos, C Pashula, D Mangan

Bibliographic record

VenueResearch into Practice: 22nd ARRB ConferenceARRB Group Limited · 2006
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsAsphaltSMA*DurabilityEngineeringForensic engineeringCivil engineeringComputer scienceGeographyArchaeology
DOInot available

Abstract

fetched live from OpenAlex

This paper describes how stone mastic asphalt (SMA) came to Australia from Europe in the early 1990s, around the same time that it was introduced to the USA and Canada, because of its’ combined good surface texture and low-noise characteristics with rut resistance and durability. While SMA and its variations now dominate asphalt surfacing types used in Europe and the United Kingdom as well as being used extensively in other parts of the world, asphalt surfacing types developed for cool European climates and heavily bound pavement types do not necessarily translate directly into warm climates or readily adapt to use as thin surfacings on flexible granular pavements. SMA projects have now been in service in Australia for periods of up to ten years. Experience has been mostly positive, however, some problems have been encountered and the additional manufacturing and placement requirements of SMA compared to dense graded asphalt have resulted in extensive research and development with inputs from German and US experts. This paper provides an update on the development of local guidelines and specifications and some of the learning experiences in adapting the SMA concepts to the Australian operating environment.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
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 head0.055
GPT teacher head0.377
Teacher spread0.322 · 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 designSimulation or modeling
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
Published2006
Admission routes1
Has abstractyes

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Same venueResearch into Practice: 22nd ARRB ConferenceARRB Group LimitedSame topicAsphalt Pavement Performance EvaluationFrench-language works237,207