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Record W4205737339 · doi:10.1080/14680629.2021.2017330

RILEM TC 279 WMR round robin study on waste polyethylene modified bituminous binders: advantages and challenges

2022· article· en· W4205737339 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.

Bibliographic record

VenueRoad Materials and Pavement Design · 2022
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsÉcole de Technologie Supérieure
FundersJavna Agencija za Raziskovalno Dejavnost RSSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen ForschungNational Science Foundation
KeywordsPolyethyleneAsphaltMaterials scienceRound robin testGeotechnical engineeringComposite materialWaste managementEngineeringMathematics

Abstract

fetched live from OpenAlex

Inter-laboratory experiments were designed to evaluate the impact of plastic waste blended directly in bitumen and to assess the properties, using conventional and advanced bituminous binder testing. The blends targeted 5% of plastic waste in 95% bitumen, using two types of polyethylene (PE) primary (pellets) and secondary (shreds) waste. The experiments showed that the addition of PE waste to bitumen does not alter the chemistry of the bitumen, the blending is physical. The DSR results indicate a strong dependency on the testing temperature as at low temperatures the composite material bitumen and PE behave both elastically whereas, at higher temperatures, the bitumen becomes viscoelastic. The MSCR tests indicated that the neat binder is more sensitive to permanent deformation compared to the blends with PE. The fatigue performance using the Linear Amplitude Sweep test showed a better performance in terms of stress and fatigue life for the PE blends.

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 categoriesMeta-epidemiology (narrow)
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 score0.112
Threshold uncertainty score1.000

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 head0.072
GPT teacher head0.260
Teacher spread0.187 · 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