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Record W2799688855 · doi:10.1520/acem20170125

Performance of Ground-Glass Pozzolan as a Cementitious Material—A Review

2018· article· en· W2799688855 on OpenAlexaff
Ahmed Omran, Nancy Soliman, Ablam Zidol, Arezki Tagnit‐Hamou

Bibliographic record

VenueAdvances in Civil Engineering Materials · 2018
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsUniversité de Sherbrooke
Fundersnot available
KeywordsPozzolanCementitiousMaterials scienceComposite materialGlass recyclingPortland cementCement

Abstract

fetched live from OpenAlex

Abstract Ground-glass pozzolan (GP) obtained by grinding the mixed-waste glass to a similar fineness as cement can act as a supplementary cementing material (SCM), given that it is an amorphous and a pozzolanic material. The GP showed promising performance in mortar and concrete mixtures in laboratory and in large-scale field applications, enabling it to be a useful new SCM. However, while there are results about the use of GP in mortar and concrete, there is no single study covering all the aspects of using GP in mortar and concrete that satisfies the requirements of the ASTM and CSA Standard Specifications. This review on the use of GP in mortar and concrete compiles and analyzes the available data concerning the characteristics, production rates, and performance of GP used in mortar and concrete to provide the necessary information for updating the ASTM and CSA Standard Specifications to consider the GP as a new SCM.

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.008
GPT teacher head0.251
Teacher spread0.243 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations46
Published2018
Admission routes1
Has abstractyes

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