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Record W2400427052 · doi:10.21809/rilemtechlett.2016.6

Recent update on the environmental impact of geopolymers

2016· article· en· W2400427052 on OpenAlexaff
Guillaume Habert, Claudiane Ouellet‐Plamondon

Bibliographic record

VenueRILEM Technical Letters · 2016
Typearticle
Languageen
FieldEngineering
TopicConcrete and Cement Materials Research
Canadian institutionsÉcole de Technologie Supérieure
Fundersnot available
KeywordsCarbon footprintLife-cycle assessmentGreenhouse gasEmbodied energyPortland cementEnvironmental impact assessmentProduction (economics)CementEnvironmental scienceBuilding materialEnvironmental economicsWaste managementCivil engineeringEngineeringMaterials scienceEconomicsGeologyPolitical science

Abstract

fetched live from OpenAlex

The contribution of building materials’ production to environmental impacts becomes significant in the new energy efficient buildings that are currently built. Among those materials, cement represents a major part of the embodied carbon footprint of buildings. Development of alternatives to traditional Portland cement have emerged over the last decades; however, their environmental assessment over their life cycle have resulted in conflicting results, which give a confusing picture of the strategic path to be followed. This paper focuses on the alkali-activated cement and concrete and points out the variability linked with the choice of energy source for the production of the activators and precursors. A review of existing studies is then performed in order to highlight the main benefits of these alternative cements in terms of reduction of greenhouse gas emissions. Finally, the results presented here highlight further research trends for new cements and concrete.

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)0.002
metaresearch head score (Gemma)0.003
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 score0.010
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0000.001
Scholarly communication0.0020.003
Open science0.0010.001
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0100.004

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 head0.010
GPT teacher head0.233
Teacher spread0.223 · 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

Citations312
Published2016
Admission routes1
Has abstractyes

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