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Record W4240884689 · doi:10.32920/ryerson.14661420

Durability of Cement Paste with Metakaolin

2021· preprint· en· W4240884689 on OpenAlexaff
Peter Mikhailenko

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsMetakaolinPortlanditeMaterials scienceCementCalcinationComposite materialPozzolanMetallurgyCarbonationPorosityPortland cementChemistry

Abstract

fetched live from OpenAlex

Durability characteristics of cement paste with two types of metakaolin (MK1 and MK2) replacement were examined. "Fluidized bed" calcination produced MK1 which was relatively pure, while "flash" calcination produced MK2, which had a high amount of quartz mixed in. At a 50% replacement after 28 days, porosity increased by 8.9 and 7% for MK1 and MK2 while primary sorptivity decreased. Thermogravometric and XRD analysis showed a decrease in the portlandite content by 79 and 75% for MKI and MK2, while the CaCO3 level did not change significantly. MK2, at an optimal replacement range of 5-30% produced relatively more CSH than MK1. Observed by SEM, metakaolin particles in MK2 were consumed by the pozzolanic activity more thoroughly than the particles of quartz. Metakaolin replacement levels of 20% or more for MK1, and 25% or more for MK2, made the cement paste very susceptible to carbonation ingress. Hydration stopping with propan-2-ol appeared to cause cracking while freeze-drying worked with no apparent problems. M

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 score0.001
Threshold uncertainty score0.004

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 head0.023
GPT teacher head0.245
Teacher spread0.221 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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