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Record W4241998843 · doi:10.32920/16732957.v2

Effect of sample geometry and aggregate type on expansion due to alkali-silica reaction

2021· preprint· en· W4241998843 on OpenAlexafffund
Noura Sinno, Medhat Shehata

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAlkali metalAlkali–aggregate reactionAlkali–silica reactionLeaching (pedology)Aggregate (composite)PrismMaterials scienceMineralogyComposite materialChemistryGeologyOpticsSoil sciencePhysicsSoil water

Abstract

fetched live from OpenAlex

Late expansions due to alkali-silica reaction were observed in field samples for some aggregates and supplementary cementing materials (SCM) combinations despite meeting the 2-year expansion criterion of the concrete prism test. This fosters a research into the effect of sample geometry and aggregate reactivity on alkali leaching and expansion of lab samples. Larger samples showed less leaching compared to standard prisms. Cylinders of 100 mm-diameter showed higher expansion than 75 mm-standard prisms; however, both sample shapes showed similar expansions for one tested aggregate when used with SCM. Alkali leaching from concrete samples and alkali release from some aggregates could lead to cylindrical samples having higher expansion and better correlation to field samples compared to standard concrete prisms.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.015
GPT teacher head0.279
Teacher spread0.263 · 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

Citations1
Published2021
Admission routes2
Has abstractyes

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