MétaCan
Menu
Back to cohort
Record W2058044418 · doi:10.1139/l05-090

Effect of coarse aggregate size on strength and workability of concrete

2006· article· en· W2058044418 on OpenAlexvenueno aff
Peter J. Tumidajski, Bingyuan Gong

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2006
Typearticle
Languageen
FieldEngineering
TopicInnovations in Concrete and Construction Materials
Canadian institutionsnot available
Fundersnot available
KeywordsCompressive strengthSlumpCementMaterials scienceWater–cement ratioAggregate (composite)Composite materialCrushed stoneGeotechnical engineeringGeology

Abstract

fetched live from OpenAlex

The properties of concrete were studied when the proportions of 37.5 and 19.5 mm stone in the coarse aggregate were varied. With the cement content of 160 kg/m 3 and the ratio of water/cement (w/c) greater than 0.9, the compressive strength is maximum at 25 percent by weight (w/o) of 37.5 mm stone. Conversely, for the cement content of 350 kg/m 3 and w/c ratios of less than 0.50, maximum compressive strength is substantively reduced. For both 160 kg/m 3 and 350 kg/m 3 cement contents, workability improves slightly as the proportion of the 37.5 mm stone is increased. For 100 mm fixed slumps and cement content of less than 160 kg/m 3 , there was little change in compressive strength as the proportion of 37.5 mm stone increased. However, when cement content was increased from 190 to 350 kg/m 3 , maximum compressive strength was observed, which shifted downward from 50 w/o to 25 w/o of 37.5 mm stone. In general, to maintain a 100 mm slump, water demand decreased as the proportion of 37.5 mm stone in the coarse aggregate fraction increased.Key words: concrete, compressive strength, workability, slump, aggregate, size, cement.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.641
Threshold uncertainty score0.468

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.003
GPT teacher head0.176
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

Citations32
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicInnovations in Concrete and Construction MaterialsFrench-language works237,207