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Record W2960998055 · doi:10.1139/cjce-2018-0571

A reality-based energy analysis of high-performance residences: Part I

2019· article· en· W2960998055 on OpenAlexaffvenue
Eric Wilson, Phalguni Mukhopadhyaya, Milad Mahmoodzadeh, Kevin Pickwick, Terry Bergen

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsRead Jones Christoffersen (Canada)University of Victoria
Fundersnot available
KeywordsResidenceEnergy performanceBuilding codeBenchmark (surveying)Architectural engineeringCode (set theory)Floor planEnergy (signal processing)Plan (archaeology)Efficient energy useCivil engineeringEngineeringComputer scienceEngineering drawingStatisticsMathematicsGeography

Abstract

fetched live from OpenAlex

This research initiative attempts to empirically determine, with reality-based (real instead of modeled) performance data from energy suppliers, the energy advantage associated with building high performance residence in Victoria, BC. In addition, this initiative created a much-needed benchmark for contractors to gain a firm understanding of the construction details required to achieve the various levels of the “Step Code” in the newest edition of the British Columbia Building Code. This was accomplished through a comparative energy analysis between a case-study high-performance “above-code residence” (ACR) to a “minimum code residence” (MCR) with the same floor plan. The ACR was built in 2015 before the step code was introduced, and therefore it was not determined what step level it achieved when it was built. It was not built to any particular performance standard, rather it was built using design details that were calculated to exceed Part 9 performance in effective R-value and airtightness. Upon investigation it was determined that the ACR achieved a performance level of “Step 3” bordering on “Step 4” performance. When compared to the MCR, it was found that the ACR has an energy advantage of 22.5 kWh/m 2 /year. However, many of the components in the ACR assemblies were either for aesthetic appeal (metal-roofing), or comfort (floor-cavity insulation), and therefore it was possible to remove these components (which is important for Part II of this study: An in-depth cost analysis between the two residences) while maintaining an energy advantage of 15 kWh/m 2 /year and step level 3 designation. This was dubbed the hybrid-residence as it employed a combination of above-code and minimum-code construction assemblies.

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)0.000
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: Empirical
Teacher disagreement score0.080
Threshold uncertainty score0.935

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
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 head0.006
GPT teacher head0.168
Teacher spread0.162 · 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

Citations2
Published2019
Admission routes2
Has abstractyes

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