MétaCan
Menu
← Back to cohort
Record W3040958195 · doi:10.1139/cjce-2020-0037

Microscopic reaction process of cement with asphalt emulsion and its influence on macroscopic properties of binder

2020· article· en· W3040958195 on OpenAlexvenueno aff
Xiaoge Tian, Huitong Yuan, Xiaofei Wang, Xuqiang Sun, Zhijun Zhang

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicAsphalt Pavement Performance Evaluation
Canadian institutionsnot available
FundersNational Natural Science Foundation of China
KeywordsAsphaltDynamic shear rheometerMaterials scienceEmulsionCementComposite materialScanning electron microscopeRheometerMicrostructureFourier transform infrared spectroscopyHydration reactionRutChemical engineeringRheology

Abstract

fetched live from OpenAlex

This research aimed at studying the reaction process between cement and asphalt emulsion from a microscopic view and the variations of macroscopic properties with cured time. The microstructure of cement asphalt emulsion (CAE) with a mass ratio of cement to asphalt (C/A) of 0.6 was scanned with scanning electron microscope (SEM) and its functional groups were measured with Fourier-transform infrared spectrometer (FTIR) after being cured for 7 days. Six CAEs with different C/A ratios were prepared and cured for different days, then DSR tests and beam bend rheometer (BBR) tests were conducted to evaluate their macroscopic performance. The results indicated that emulsion residue was relatively porous. Hydration reaction occurred between cement and water secreted by demulsification of asphalt emulsion, hydrates would gradually fill the voids. Asphalt and hydrates were interrelated into a cross-linking structure. As the rigidity of hydrates increased with cured time, the rutting resistance of CAE was improved, but its low-temperature performance and fatigue resistance were reduced.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.015
GPT teacher head0.206
Teacher spread0.191 · 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

Citations7
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Civil Engineering→Same topicAsphalt Pavement Performance Evaluation→French-language works237,207→