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Record W2064915632 · doi:10.1680/macr.13.00250

Self-healing ability of cementitious composites: effect of addition of pre-soaked expanded perlite

2014· article· en· W2064915632 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

VenueMagazine of Concrete Research · 2014
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsToronto Metropolitan University
FundersTürkiye Bilimler Akademisi
KeywordsPerliteMaterials scienceComposite materialUltimate tensile strengthCompressive strengthCementitiousPermeability (electromagnetism)ChlorideAggregate (composite)CementMetallurgyChemistryMembrane

Abstract

fetched live from OpenAlex

This study assessed the use of pre-soaked expanded perlite aggregate (PS-EPA) on the self-healing of cementitious composites by replacing a proportion of normal aggregate with PS-EPA at different replacement rates. Specimens with and without PS-EPA were stored in water for 28 d and then mechanical loading was applied to produce specimen deterioration. At the age of 28 d, pre-loaded and sound specimens were exposed to continuous air (CA) exposure for 30 d. The degree of deterioration as a result of mechanical pre-loading and the degree of self-healing were determined via characterisation of crack numbers and widths, transport (chloride ion permeability) and mechanical properties (splitting tensile strength), and specimens with and without PS-EPA were compared. The test results revealed that increased PS-EPA content significantly improved the compressive strength and chloride ion permeability of specimens, and that it further enhanced the hydration and healing capability of specimens under CA exposure after pre-loading.

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)0.004
metaresearch head score (Gemma)0.001
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 score0.028
Threshold uncertainty score0.818

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.016
GPT teacher head0.300
Teacher spread0.283 · 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