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Record W2170144458 · doi:10.1139/l07-111

Relationship between methylene blue values of concrete aggregate fines and some concrete properties

2008· article· en· W2170144458 on OpenAlexvenueno aff
İlker Bekir Topçu, Abdullah Demi̇r

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2008
Typearticle
Languageen
FieldEngineering
TopicInnovative concrete reinforcement materials
Canadian institutionsnot available
Fundersnot available
KeywordsAggregate (composite)Sieve (category theory)Materials scienceCompressive strengthMortarSlumpAbrasion (mechanical)Composite materialMethylene blueGeotechnical engineeringGeologyChemistryMathematics

Abstract

fetched live from OpenAlex

The fine granular structure and surface activity of clay minerals increase the amount of mixing water needed to provide workability in concrete. Even when the microfine material percentage in fine aggregate is low, the methylene blue value of the fine aggregate increases when materials of clay origin are present. In this study, methylene blue values were determined in fine aggregate samples used to produce ready-mixed concrete. Samples were taken from four different aggregate quarries, and relationships between methylene blue values of the concrete samples produced with these aggregates and some of their properties were investigated. Tests were done to determine the quality of microfine material (i.e., passing 0.063 mm sieve). Slump, ultrasonic pulse velocity, compressive strength, and surface abrasion resistance tests were performed on concretes made with these aggregate fines. It is shown that clay content, as indicated by the methylene blue value test, affects the concrete properties, but the microfine material percentage does not give any hint about clay content.

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 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 score0.239
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.033
GPT teacher head0.206
Teacher spread0.173 · 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 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

Citations14
Published2008
Admission routes1
Has abstractyes

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