MétaCan
Menu
Back to cohort
Record W190840936

EVALUATION OF WELL-GRADED AND FINE-GRADED ASPHALT MIXES USING THE INDIRECT TENSILE TEST AND THE RESILIENT MODULUS TEST

2004· article· en· W190840936 on OpenAlexaboutno aff
Ahmed Shalaby, Teik Hua Law, Amir Kavussi

Bibliographic record

VenueIJP. International journal of pavements · 2004
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsGradationAsphaltUltimate tensile strengthMaterials scienceStiffnessDynamic modulusComposite materialTensile testingAsphalt concreteService lifeModulusAsphalt pavementStructural engineeringGeotechnical engineeringEngineeringComputer scienceDynamic mechanical analysis
DOInot available

Abstract

fetched live from OpenAlex

In this paper, the material properties of two commonly used asphalt paving mixes are evaluated. Bituminous B (Bit B) is a well graded mix and traditionally has exhibited good wearing resistance while Bituminous C (Bit C) has a lower asphalt content and can be classified as fine graded mix. A volumetric analysis was conducted on the two mixes which revealed certain differences in gradation, asphalt content, and voids ratio. The indirect tensile test (IDT) and the resilient modulus test were employed to evaluate both the static and dynamic responses. The tests were conducted on asphalt concrete cores extracted from several in service project sites throughout Manitoba. The IDT determined the tensile strength and the stiffness at 25% of the failure load, while dynamic loading was used to determine the resilient modulus at various operating temperatures. These protocols represent the initial steps towards the implementation of mechanistic design procedures in Manitoba and will improve the characterization of asphalt paving mixtures.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.035
Threshold uncertainty score0.397

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
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 head0.032
GPT teacher head0.295
Teacher spread0.263 · 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

Citations0
Published2004
Admission routes1
Has abstractyes

Explore more

Same venueIJP. International journal of pavementsSame topicAsphalt Pavement Performance EvaluationFrench-language works237,207