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Record W2048227614 · doi:10.1139/l99-068

Experience with alkali-aggregate reaction in the Canadian prairie region

2000· article· en· W2048227614 on OpenAlexfundvenueaboutno aff
STR Roy, J. A. Morrison

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2000
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsnot available
FundersManitoba Hydro
KeywordsAlkali–aggregate reactionAggregate (composite)Forensic engineeringCrackingMortarEnvironmental scienceEngineeringArchaeologyGeographyMaterials scienceComposite material

Abstract

fetched live from OpenAlex

This paper summarizes alkali-aggregate reaction (AAR) experience in the prairie region to date. Information is presented on reactive rock types and their geological significance, laboratory test data, field evidence of affected structures, and industry practices for preventive measures and management of affected structures. The frequency and severity of documented AAR-affected structures in Manitoba, Saskatchewan, and Alberta is low, Alberta having the highest incidence. A significant number of aggregate sources in the region show potential for excessive expansion when subjected to laboratory testing. The lack of field evidence is generally attributed to the lower alkali contents of cements that have historically been produced and used in the region. Limited number and extent of searches for affected structures, inadequate diagnosis of the phenomenon, and client confidentiality are also factors. It is imperative that specifiers, owners, researchers, suppliers, and producers be aware of the potential reactivity of local aggregates. The occurrences of AAR-related deterioration in the field demonstrates that the phenomenon is not limited to the laboratory. The effectiveness of low to moderate alkali contents of concrete mixtures in controlling the AAR phenomenon demonstrates the need to specify low-alkali cement and the importance of measuring the effectiveness of supplementary cementing materials in preventing AAR. There is a need to conduct extensive field searches for affected structures and it is important that suspected cases of AAR be properly diagnosed.Key words: alkali-aggregate reaction, concrete, Manitoba, Saskatchewan, Alberta, laboratory testing, field evidence, pattern cracking, prisms, mortar bars, prevention, management.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.059
Threshold uncertainty score0.118

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0080.003
Scholarly communication0.0010.001
Open science0.0020.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.204
Teacher spread0.192 · 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 designObservational
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

Citations5
Published2000
Admission routes3
Has abstractyes

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