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Record W2185486082

Life Cycle Assessment for Sustainable Design of Precast Concrete Commercial Buildings in Canada

2012· article· en· W2185486082 on OpenAlexaboutno aff
Medgar L. Marceau, Lindita Bushi, Jaime Meil, Matthew Francis Bowick, Morrison Hershfield

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsPrecast concreteLife-cycle assessmentContext (archaeology)Building envelopeCivil engineeringSustainabilityEngineeringEmbodied energyMasonry veneerEnvironmental impact assessmentArchitectural engineeringCurtain wallMasonryProduction (economics)
DOInot available

Abstract

fetched live from OpenAlex

2 Athena Sustainable Materials Institute Abstract: A life cycle assessment (LCA) was conducted on a typical five-storey commercial building with five variations of exterior wall system and two variations of climate and location. The goal of the LCA was to gain a better understanding of precast concrete's environmental performance in the context of whole buildings. LCA is an analytical tool to comprehensively quantify and interpret the energy and material flows to and from the environment over the life of a product, process, or service. The energy and material flows are the environmental emissions to air, land, and water, and the consumption of energy and material resources. This paper presents the cradle-to-grave LCA of precast concrete commercial buildings with precast structure and precast wall envelope, relative to alternative wall envelope systems. Because the LCA includes a public comparative assertion, the study was critically reviewed by an independent external committee of LCA experts to ensure the LCA is consistent with the requirements of international ISO standards on LCA. The results show that over the full life cycle, the buildings with precast concrete walls have less environmental impact than the buildings with masonry brick veneer walls and those with glass and aluminum curtain wall, all other factors being equal.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.605
Threshold uncertainty score0.746

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.246
Teacher spread0.231 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations8
Published2012
Admission routes1
Has abstractyes

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