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Record W2338758369 · doi:10.14288/1.0077966

Life cycle analysis : the Richmond Olympic Oval Vancouver, British Columbia

2012· article· en· W2338758369 on OpenAlexaboutno aff
Clare Zemcov, Radu Postole, Darren Thomas

Bibliographic record

VenuecIRcle (University of British Columbia) · 2012
Typearticle
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsHistory

Abstract

fetched live from OpenAlex

This report is the result of a Life Cycle Assessment study performed on the Richmond Olympic Oval skating rink in Richmond, British Columbia. This study has been completed in conjunction with one other Olympic venue skating rink located at the University of British Columbia, and encompasses the building envelope and structure from cradle to gate. The ultimate goal of this study is to act as a benchmark for future LCA studies conducted on Olympic venues of similar function, as well as to contribute to the general body of knowledge for LCA studies conducted on structures and envelopes. With the use of two computer programs, environmental impacts have been determined through the measurement and quantification of materials consumed in the construction of the rink. From the bill of materials, the five largest quantities were 30 MPa concrete, ballast (aggregate stone), softwood lumber, rebar (rod and light sections) and Rockwool Batt insulation. The resulting summary measures table by life cycle stage was then used for sensitivity analyses and building performance. A sensitivity analysis was conducted on five building materials, and illustrated how the building’s overall impact on the environment changed as the quantity of each material increased by 10%. The results demonstrate that the impact categories are consistently most sensitive to a 10% increase in concrete. Rebar caused the second highest change overall; and other materials considered generally created minimal relative change in the sensitivity analysis. [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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.068
Threshold uncertainty score0.167

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0020.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.004
GPT teacher head0.153
Teacher spread0.149 · 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
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
Published2012
Admission routes1
Has abstractyes

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