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Record W2160461030 · doi:10.1139/l09-140

Integration of carbon sequestration into curing process of precast concrete

2010· article· en· W2160461030 on OpenAlexaffvenueabout
Sean Monkman, Yixin Shao

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsMcGill University
Fundersnot available
KeywordsCarbonationPrecast concreteCuring (chemistry)Flue gasEnvironmental scienceWaste managementCarbon dioxideCarbon sequestrationCompressive strengthMaterials scienceComposite materialEngineeringChemistryCivil engineering

Abstract

fetched live from OpenAlex

The feasibility of integrating carbon sequestration into the curing of precast concrete products was investigated. Research assessed the CO 2 uptake capacities of carbonation-cured concrete masonry units (CMU), concrete pavers, fibreglass-mesh reinforced cement board, cellulose-fibre board, and ladle slag fines. Three curing systems were used: (i) an open-inlet system using pressurized recovered CO 2 ; (ii) a closed system using pressurized flue gas with 14% CO 2 ; and (iii) a closed system using dilute CO 2 under atmospheric pressure. The amount of carbon dioxide that could be sequestered in the annual North American output of the various precast concrete products was estimated. The net efficiency was calculated accounting for CO 2 emissions penalty resulting from the capture, compression, and potential transport of the curing gases. Carbonation curing of the considered products could result in a net annual CO 2 sequestration in US and Canada of approximately 1.8 million tonnes if recovered CO 2 is used and one million tonnes if flue gas is used.

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)0.000
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.007
GPT teacher head0.214
Teacher spread0.207 · 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 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

Citations103
Published2010
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicCO2 Sequestration and Geologic InteractionsFrench-language works237,207