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Record W4409320264 · doi:10.1080/14680629.2025.2486524

Assessing the blending of recycled LDPE flakes with bitumen in mixtures using rheological and thermal properties: a case study

2025· article· en· W4409320264 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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueRoad Materials and Pavement Design · 2025
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsÉcole de Technologie Supérieure
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRheologyAsphaltMaterials scienceLow-density polyethyleneComposite materialThermalPolyethylene

Abstract

fetched live from OpenAlex

Despite growing interest in asphalt mixtures modified with low-density polyethylene (LDPE), the industry lacks clear guidelines to reliably produce these materials, particularly with the dry method where the role of melted plastic particles is unclear. This paper assesses the blending potential of recycled LDPE flakes with bitumen introduced by the dry method and develops a methodology to estimate how much plastic functions as a binder modifier. Five mixtures were compared: four laboratory-produced mixtures (0% and 1% LDPE, unaged and short-term aged) and one plant-produced mixture with 1% LDPE. Bitumens were extracted and recovered (E&R) to evaluate LDPE presence through rheological and thermal analyses. The results indicated that most LDPE remained dispersed as fibres/particles with aggregate, but a small fraction systematically modified the binder, notably in plant-produced mixtures. Workability testing further suggested LDPE primarily functions as a mixture modifier rather than as a bitumen modifier in the dry process.

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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.207
Threshold uncertainty score0.328

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.065
GPT teacher head0.304
Teacher spread0.239 · 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