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Record W2072052041 · doi:10.1680/macr.2003.55.6.517

Effects of curing temperature on moisture distribution, drying and water absorption in self-compacting concrete

2003· article· en· W2072052041 on OpenAlexaff
P. F. de J. Cano-Barrita, Theodore W. Bremner, Bruce J. Balcom

Bibliographic record

VenueMagazine of Concrete Research · 2003
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsSorptivityCuring (chemistry)MoistureMaterials scienceDurabilityComposite materialAbsorption of waterWater contentPenetration (warfare)Geotechnical engineering

Abstract

fetched live from OpenAlex

Steam curing is normally used in the precast industry to increase the rate of strength development with the aim of reducing the cycle time and thereby increasing productivity. However, there is concern about the durability of steam cured concrete elements, which is mainly determined by the quality of the cover concrete. In an effort to evaluate the effectiveness of curing at 50°C for several hours in producing durable concrete, compared to moist curing at 23 and 38°C for seven days, the moisture distribution of drying self-compacting concrete containing 30% fly ash, as well as the moisture distribution in water uptake experiments were studied using magnetic resonance imaging. The results of drying indicated an increased moisture loss in the cover concrete when the specimens were cured at 50°C. The water uptake experiments showed a higher penetration of the water front, higher sorptivity, and higher moisture diffusivity of concrete cured at 50°C compared to concrete which was moist cured at 38°C.

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)0.001
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 score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 head0.013
GPT teacher head0.271
Teacher spread0.258 · 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

Citations15
Published2003
Admission routes1
Has abstractyes

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