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Record W2046508501 · doi:10.1139/l04-065

Comparing back-calculated and laboratory resilient moduli of bituminous paving mixtures

2004· article· en· W2046508501 on OpenAlexvenueaboutno aff
Ahmed Shalaby, T Liske, Amir Kavussi

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2004
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
FundersDivision of Materials Research
KeywordsFalling weight deflectometerAsphaltDeflection (physics)Structural engineeringGeotechnical engineeringStiffnessAsphalt concreteModulusUltimate tensile strengthEngineeringMaterials scienceComposite material

Abstract

fetched live from OpenAlex

The stiffness of bituminous mixes is an important indicator of mix performance and a required input for mechanistic pavement design. Resilient modulus is one of many stiffness indicators of mixes which can be determined using laboratory testing methods or non-destructive field tests such as falling weight deflectometer (FWD) tests through back calculation. In this paper, two Manitoba mixes known as Bituminous B (Bit B) and Bituminous C (Bit C) are analysed using laboratory testing and FWD back calculation. The experiment involved samples from eight paving sites. Each site included two side-by-side sections having a common Bit B surface course over either a Bit B or a Bit C binder course. Cored samples were tested following the guidelines of the long term pavement performance protocol P07 at 5, 25, and 40 °C. The modulus of each layer was also estimated from FWD deflection measurements. Findings include correlations between the various material and test parameters and a comparison between back calculated and laboratory stiffnesses.Key words: falling weight deflectometer, indirect tensile test, resilient modulus, asphalt concrete.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.238
Threshold uncertainty score0.650

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 head0.010
GPT teacher head0.191
Teacher spread0.181 · 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

Citations21
Published2004
Admission routes2
Has abstractyes

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