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Record W2009275598 · doi:10.1680/adcr.12.00054

Early carbonation behaviour of no-clinker steel slag binder

2013· article· en· W2009275598 on OpenAlexaff
Zhen He, Huamei Yang, Yixin Shao, Meiyan Liu

Bibliographic record

VenueAdvances in Cement Research · 2013
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsMcGill University
Fundersnot available
KeywordsCarbonationMaterials scienceMetallurgyCalcium hydroxideSlag (welding)CementClinker (cement)Scanning electron microscopeCompressive strengthComposite materialPortland cementChemical engineering

Abstract

fetched live from OpenAlex

The use of steel slag as a no-clinker binder was studied. Steel slag was activated by CO2 to develop strength as a cementing material for building product applications. The performance of slag paste compacts formed by low water to slag ratio was characterised by X-ray diffraction analysis, thermal analysis and field emission scanning electron microscopy analysis affiliated with energy dispersive spectrometer analysis. Results showed that the mineral components of steel slag, such as calcium hydroxide and calcium silicates (C3S and C2S), were CO2 reactive. The reaction products were strength contributing. Immediate carbonation of 2 h was capable of developing rapid early strength while promoting subsequent hydration. The reaction products of steel slag after carbonation and hydration were the combination of poorly crystalline CaCO3 intermingled with C-S-H gel, which was the characteristic of the early hardening structure of no-clinker steel slag.

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 score0.006

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)0.0020.000

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 head0.036
GPT teacher head0.345
Teacher spread0.309 · 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

Citations9
Published2013
Admission routes1
Has abstractyes

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