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Record W2082406550 · doi:10.1139/l99-076

Alkali-aggregate reactivity in Québec (Canada)

2000· article· en· W2082406550 on OpenAlexvenueaboutno aff
Marc-André Bérubé, Daniel Vézina, Benoît Fournier

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2000
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsnot available
Fundersnot available
KeywordsAlkali–silica reactionSilica fumeAggregate (composite)Alkali–aggregate reactionFly ashCementReactivity (psychology)Alkali metalLimitingMaterials scienceMortarEnvironmental scienceWaste managementComposite materialEngineeringChemistryMechanical engineering

Abstract

fetched live from OpenAlex

In the province of Québec, due to the particular geology and the historic use of high-alkali cements, a large number of concrete structures are affected by alkali-silica reactivity (ASR). Consequently, tremendous effort was made in this province during the last 20 years on (1) the determination in the laboratory (testing methods) as well as in the field (inspection of structures) of the potential alkali-aggregate reactivity (AAR) of concrete aggregates, (2) the prevention of AAR in new structures, and (3) the management of existing structures affected by this problem. For new structures, the most popular measure used in Québec in the presence of potentially reactive aggregates consists of limiting the alkali contribution by the cement to 3 kg/m 3 of concrete (Na 2 O eq ). Also, blended silica fume cements were used on many occasions against ASR; ternary cements containing fly ash and silica fume, which proved in the laboratory to be effective against ASR, are presently available. As concerns the existing structures affected by ASR, many of them were repaired using various techniques ranging from the simple application of a penetrating sealer to the application of post-constraints or slot cutting.Key words: aggregate, alkali-aggregate reaction, cement, concrete, diagnosis, management, preventive measures, prognosis, Québec, testing.

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 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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.887
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

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)0.0020.000

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 head0.007
GPT teacher head0.181
Teacher spread0.174 · 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 teacher head, not a consensus.

Study designNot applicable
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

Citations28
Published2000
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicConcrete and Cement Materials ResearchFrench-language works237,207