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Record W1976757067 · doi:10.1680/macr.13.00222

Dynamic carbonation curing of fresh lightweight concrete

2014· article· en· W1976757067 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueMagazine of Concrete Research · 2014
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCarbonationCarbon dioxideCuring (chemistry)CarbonatationMaterials scienceRelative humidityComposite materialEnvironmental scienceWaste managementChemistryEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

The reaction of fresh lightweight concrete with carbon dioxide during early-age carbonation curing is hindered by surface saturation due to vibration consolidation. To promote a high degree of carbonation of fresh lightweight concretes, a dynamic carbonation system was developed to remove surface free water and inject carbon dioxide simultaneously. Based on cement mass, the resulting carbon uptake reached 13% in 4 h carbonation and 20% in 18 h carbonation. The early strength by fresh carbonation is comparable to that of steam curing, while the late strength is higher in a much reduced process time. The dynamic system can effectively control the relative humidity of the chamber to prevent water accumulation and create a route of capillaries for carbon dioxide diffusion and precipitation of carbonates. Dynamic carbonation creates a carbonate–bond matrix. The process provides an excellent means to recycle carbon dioxide, with economic and environmental benefits.

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.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.149
Threshold uncertainty score0.841

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.020
GPT teacher head0.294
Teacher spread0.273 · 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