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Record W2044211161 · doi:10.1520/jte100475

Deicer Salt Scaling Resistance of Concrete Containing Manufactured Sands

2006· article· en· W2044211161 on OpenAlexaff
Ufuk Dilek, ML Leming

Bibliographic record

VenueJournal of Testing and Evaluation · 2006
Typearticle
Languageen
FieldEnvironmental Science
TopicSmart Materials for Construction
Canadian institutionsStantec (Canada)
Fundersnot available
KeywordsAggregate (composite)Geotechnical engineeringMaterials scienceGeologyMetallurgyComposite material

Abstract

fetched live from OpenAlex

Abstract Manufactured sands are produced by crushing rock deposits to produce a fine aggregate which is generally more angular and has a rougher surface texture than naturally weathered sand particles. Manufactured sands can also contain significant quantities of rock dust. As natural sand deposits become depleted near some areas of metropolitan growth, the use of manufactured sands as a replacement fine aggregate in concrete is receiving attention. Designers, specifiers, contractors, and material suppliers need to understand the effects of manufactured sand particle shape characteristics and angularity as well as fines content on concrete water demand and concrete durability, including the effects of interrelationships between manufactured sand characteristics. As part of a comprehensive research program, manufactured sand properties and their effects on fresh concrete properties, mechanical properties and concrete durability were investigated. Concrete containing commercially available manufactured sands with a wide range of particle angularities and fines contents were included in the laboratory testing program on deicer salt scaling. Angularity of particles and quantity of fines were found to contribute to salt scaling.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.475
Threshold uncertainty score0.189

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0000.000

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 head0.024
GPT teacher head0.264
Teacher spread0.240 · 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.

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
Published2006
Admission routes1
Has abstractyes

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