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Record W2016622589 · doi:10.1520/cca10532j

Is ASTM C 672 Curing Procedure Still Appropriate to Test the Scaling Resistance of Blended Cements?

2002· article· en· W2016622589 on OpenAlexaff
Mladenka Saric-Coric, P-C Aïtcin

Bibliographic record

VenueCement Concrete and Aggregates · 2002
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsCuring (chemistry)Materials sciencePortland cementCementScalingComposite materialSlag (welding)MetallurgyMathematics

Abstract

fetched live from OpenAlex

Abstract The scaling resistance of slag-blended cements can be critical when tested according to the procedure described in the present ASTM C 672 standard. As soon as slag replacement is greater than 20 percent, the scaling resistance of concretes made with a slag-blended cement deteriorates rapidly. But when the initial water curing procedure is lengthened from 13 to 27 days, the slag-blended samples have enough time to become more fully mature and they easily pass the scaling test, even when the substitution rate is as high as 80 percent. Lengthening of the present initial water-curing period from 13–27 days should be considered in the case of slag-blended cements, and most probably for other blended cements as well. This would allow for concretes made with a blended cement to reach the same degree of maturity as concretes made with pure Portland cement when they are submitted for the first time to freezing and thawing cycles in the presence of deicing salts.

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)0.003
metaresearch head score (Gemma)0.006
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 score0.003
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0000.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.003

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 head0.019
GPT teacher head0.231
Teacher spread0.211 · 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

Citations6
Published2002
Admission routes1
Has abstractyes

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