MétaCan
Menu
Back to cohort
Record W1833144677 · doi:10.1139/l10-081

Carbonation of fly ash concrete: laboratory and field data

2010· article· en· W1833144677 on OpenAlexaffvenue
N. Bouzoubaâ, A. Bilodeau, B. T. Tamtsia, S. Foo

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2010
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsPublic Works and Government Services CanadaNatural Resources Canada
Fundersnot available
KeywordsCarbonationFly ashCementitiousPortland cementRelative humidityCompressive strengthCementCarbonatationEnvironmental scienceMaterials scienceComposite materialGeotechnical engineeringGeologyMeteorology

Abstract

fetched live from OpenAlex

The present study consists of investigating the carbonation resistance of two series of concrete mixtures designed for three classes of concrete (25, 35, and 45 MPa compressive strength at 28 d) and using American Society for Testing and Materials (ASTM) type I Portland cement and two commercially used fly ashes meeting the ASTM standards at the level of 20%, 35%, and 50% of the total weight of cementitious materials. The carbonation resistance was determined on samples moist cured for 3, 7, and 10 d and exposed to a CO 2 -enriched environment (3% CO 2 at 23 °C and 65% relative humidity) for 140 d to accelerate the carbonation; it was also determined on samples moist cured for 7 d and exposed to an indoor and outdoor natural environments for 4 years. A mathematical model allowing the prediction of the depth of accelerated carbonation of fly ash concrete mixtures is presented.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.210
Teacher spread0.200 · 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 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

Citations41
Published2010
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicConcrete and Cement Materials ResearchFrench-language works237,207