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Record W2070680485 · doi:10.1139/l05-096

Comparative study of performance of natural fibres and crumb rubber modified stone matrix asphalt mixtures

2006· article· en· W2070680485 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2006
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
Fundersnot available
KeywordsAsphaltMaterials scienceComposite materialCrumb rubberRutSMA*Ultimate tensile strengthCreepAggregate (composite)Natural rubberPermeability (electromagnetism)Moisture

Abstract

fetched live from OpenAlex

Stone matrix asphalt (SMA) is a gap-graded mix that contains a high concentration of coarse aggregate, thereby maximizing stone-to-stone contact in the mixture and providing an efficient network for load distribution. Coarse aggregate particles are held together by a rich matrix of mineral filler and stabilizer in the thick asphalt film. This paper presents details on the laboratory studies carried out on stone matrix asphalt (SMA) mixtures with natural fibres and crumb rubber modified bitumen (CRMB). Indirect tensile strength, retained stability, resistance to moisture susceptibility, resistance to rutting, resistance to creep, and resistance to permeability and aging were found to improve with SMA mixtures with CRMB when compared with SMA mixtures with fibres as stabilizers.Key words: natural fibres, CRMB, SMA mixtures, draindown, moisture damage, creep, rutting, permeability, aging.

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.

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 score0.181
Threshold uncertainty score0.702

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 head0.011
GPT teacher head0.230
Teacher spread0.219 · 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