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Record W2070695831 · doi:10.3846/13923730.2012.734848

EXPERIMENTAL STUDY OF BITUMINOUS MASTIC BEHAVIOUR USING DIFFERENT FILLERS BASED ON THE UCL METHOD

2013· article· en· W2070695831 on OpenAlexaff
Diana Movilla-Quesada, Ángel Vega-Zamanillo, Miguel Ángel Calzada-Pérez, Daniel Castro‐Fresno

Bibliographic record

VenueJournal of Civil Engineering and Management · 2013
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsTransport Canada
FundersUniversidad de Cantabria
KeywordsAsphaltCalcium hydroxideDurabilityMaterials scienceFiller (materials)Composite materialAggregate (composite)HydroxideChemical engineeringEngineering

Abstract

fetched live from OpenAlex

This research demonstrates that the use of suitable amounts of calcium hydroxide as an additive in asphalt mixtures can improve the aggregate-bitumen adhesion, forming a bituminous mixture which is more resistant to traffic loads and the action of water. The analysis was performed using the UCL method and the Cantabrian Test, taking as a case study three types of filler with different natures, mixed with 4.5% bitumen. The results are presented as state curves, which show clear differences between the three fillers, demonstrating that the hydroxide suffers small wear losses in concentrations close to 1.3%, indicating a significant reduction in the risk of plastic deformation, and an improvement in the mixture durability and/or adhesiveness.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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)0.0020.000

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 head0.021
GPT teacher head0.251
Teacher spread0.231 · 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 designBench or experimental
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

Citations10
Published2013
Admission routes1
Has abstractyes

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