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Record W2282600355 · doi:10.14288/1.0108883

Life cycle assessment of the Civil and Mechanical Engineering Building

2015· article· en· W2282600355 on OpenAlexaboutno aff
Cayley Van Hemmen

Bibliographic record

VenuecIRcle (University of British Columbia) · 2015
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicLife Cycle Costing Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsEngineeringCivil engineeringArchitectural engineeringForensic engineeringConstruction engineering

Abstract

fetched live from OpenAlex

This report contains an in-depth Life Cycle Analysis of the Civil and Mechanical Engineering (CEME) Building at the University of British Columbia in Vancouver, British Columbia. The life cycle analysis scope includes the envelope and structure of CEME from cradle to gate, that is, from the building’s product manufacturing to end of construction stage. The methods used to achieve a detailed analysis included contributions from two authors. The first author included a thorough on screen takeoff of CEME’s level three elements including foundations, walls/floors above and below grade, roof structure and interior partition walls. The second contributor then assessed the quality of the initial study and made improvements to the accuracy of that study. An impact assessment was then performed on each element to determine its contribution by impact category to overall impacts for CEME as a whole. The results of the impact assessment were then compared to 22 other institutional buildings at UBC to determine how CEME equated. It was determined that CEME’s had less of an environmental impact than the majority of other buildings at UBC as it’s impact category values were lower than the benchmark’s value. Furthermore, CEME’s level three element “A23 Upper Floor Construction” contributed the most in all seven impact categories included in the Athena Impact Estimator. Finally, it was discovered that the product stage had a larger impact that the construction stage for all level three elements, it was approximately 80-90% larger in all cases. This report also includes interpretations of the results such as recommendations for LCA use to be put in practice and an author’s reflection of the project and CIVL 498C as a whole. Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report.”

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.213

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0040.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.011
GPT teacher head0.180
Teacher spread0.169 · 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 designObservational
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

Citations0
Published2015
Admission routes1
Has abstractyes

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