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Record W3091780209 · doi:10.1139/cjce-2020-0090

Effects of dosage of warm mix asphalt additive on stiffness, cracking susceptibility, and moisture sensitivity characteristics

2020· article· en· W3091780209 on OpenAlexaffvenue
Salvatory Materu, Ahmed Shalaby, Ahmed Ghazy

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsAsphaltRutCompactionCrackingMoistureMaterials scienceCementUltimate tensile strengthMixing (physics)Composite materialAsphalt pavementGeotechnical engineeringEnvironmental scienceEngineering

Abstract

fetched live from OpenAlex

Warm mix asphalt (WMA) technology has the capability of lowering asphalt mixing and compacting temperature by 30 °C or more without compromising the performance of asphalt pavement. This results to a lower cooling rate that allows for long haul, and sufficient compaction time. The objective of this study is to evaluate the effectiveness of the common chemical additives on the properties of WMA mixtures through field and laboratory testing programs. Three dosages (0.3, 0.5, and 0.7% by weight of asphalt cement) were used without changing the job mix formula. Among the different additive dosage used, 0.5% had a better overall performance. For example, the moisture sensitivity test for the 0.5% WMA indicated the highest tensile strength ratio; subsequently, low moisture damage. All WMA mixtures had low rutting resistance potential and higher cracking resistance compared to conventional mix.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.528
Threshold uncertainty score0.800

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 science0.0000.000
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 head0.008
GPT teacher head0.195
Teacher spread0.187 · 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 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
Published2020
Admission routes2
Has abstractyes

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