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Record W3117934227 · doi:10.1139/cjce-2019-0265

Correlating the cellular network, in foamed concrete containing ash, with their physical properties

2020· article· en· W3117934227 on OpenAlexafffundvenue
Jonathan Stolz, Yaman Boluk, Vivek Bindiganavile

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2020
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicBuilding materials and conservation
Canadian institutionsUniversity of Alberta
FundersUniversity of Alberta
KeywordsMaterials scienceFly ashPortland cementCementitiousPorosityComposite materialFractal dimensionThermal conductivityCementMetakaolinFractal

Abstract

fetched live from OpenAlex

Cellular concrete is a lightweight solid cementitious foam that is used mainly for thermal insulation and sound absorption. Either partially or wholly, when the Portland cement in the binder is replaced with ash, the environmental impact of the material is reduced. However, the resulting changes in the cell structure and their subsequent impact upon the physical properties of the material have not been well examined. In this study, cellular concrete was prepared from alkali activated fly ash binders and separately, from Portland cement binders blended with wood ash. The cell structure was photographed using laser confocal microscopy and the images were analyzed to quantify the cellular network in terms of the porosity and the fractal dimension of the porous phase. Alongside, the cellular concrete specimens were tested for their thermal constants and sound absorption. The results show that there was an increase in the fractal dimension and an associated drop in thermal conductivity for an increase in the porosity.

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)0.000
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 score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.015
GPT teacher head0.141
Teacher spread0.126 · 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

Citations3
Published2020
Admission routes3
Has abstractyes

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