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Record W1938789248 · doi:10.24908/pceea.v0i0.3842

DESIGN OF A WESTERN ENGINEERING "GREEN" BUILDING

2011· article· en· W1938789248 on OpenAlexaffvenueabout
Denis M. O’Carroll, Ernest K. Yanful, F. Berruti, Ralph O. Buchal

Bibliographic record

VenueProceedings of the Canadian Engineering Education Association (CEEA) · 2011
Typearticle
Languageen
FieldEngineering
TopicDesign Education and Practice
Canadian institutionsWestern University
Fundersnot available
KeywordsCapstoneAccreditationMultidisciplinary approachWork (physics)Engineering managementArchitectural engineeringEnvironmental designEngineering educationEngineeringDesign for the EnvironmentSustainable designEngineering design processEngineering ethicsCivil engineeringSustainabilityMechanical engineeringComputer scienceSociologyProduct designMedical education

Abstract

fetched live from OpenAlex

The Faculty of Engineering proposes to replace an existing building at the University of Western Ontario with a modern, state of-the-art, environmentally friendly, and energy-efficient building designed by students. This is an ideal opportunity to expose students to an interdisciplinary design project involving every engineering discipline. Students were commissioned to design a building that achieves the highest possible Leadership in Energy and Environmental Design accreditation. Initial design work was performed by students as part of their capstone design courses in 2004/2005. In 2005/2006, two competing multidisciplinary teams of students conducted detailed integrated design work in collaboration with industry - including architects and engineering consulting firms - to tackle the structural, environmental, materials, mechanical and electrical requirements. The experience was very positive, but the degree of interdisciplinary collaboration was less than expected due to the departmental nature of existing capstone design courses.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.031
Threshold uncertainty score0.062

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0100.002

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 head0.017
GPT teacher head0.202
Teacher spread0.185 · 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
Published2011
Admission routes3
Has abstractyes

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