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Record W4247681326 · doi:10.32920/16806661

The Efficacy of Accelerated Test Methods to Evaluate Alkali Silica Reactivity of Recycled Concrete Aggregates

2021· preprint· en· W4247681326 on OpenAlexafffund
Medhat Shehata, E. R. Johnson

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicRecycled Aggregate Concrete Performance
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of CanadaMinistère des TransportsUniversité Laval
KeywordsAlkali–silica reactionMortarMaterials scienceReactivity (psychology)Bar (unit)Alkali–aggregate reactionAlkali metalAggregate (composite)Test methodComposite materialChemistryGeology

Abstract

fetched live from OpenAlex

The effectiveness of accelerated tests in evaluating the Alkali-Silica Reactivity of Recycled Concrete Aggregates was evaluated. The Accelerated Mortar Bar Test was found effective for evaluating potential alkali-reactivity when the test variables, such as crushing method and absorption, are carried out in a well-defined process. The method of crushing was found to have significant impact on the expansion. The Concrete Microbar Test (CMBT) provides good correlation to the expansion of Concrete Prisms incorporating Supplementary Cementing Materials when an expansion limit of 0.10% at 56 days or 0.04% at 28 days were used, based on the limited number of tests carried out here.

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)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.206
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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 head0.038
GPT teacher head0.334
Teacher spread0.296 · 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 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

Citations0
Published2021
Admission routes2
Has abstractyes

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