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Record W2953439837 · doi:10.29173/mocs126

Consequences of the BC Energy Step Code on Offsite Construction

2019· article· en· W2953439837 on OpenAlexaffvenueabout
Guido Wimmers, Alison Conroy

Bibliographic record

VenueModular and Offsite Construction (MOC) Summit Proceedings · 2019
Typearticle
Languageen
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsUniversity of Northern British Columbia
Fundersnot available
KeywordsSustainabilityEfficient energy useBuilding codeBuilding envelopeArchitectural engineeringConstruction industryNorm (philosophy)Civil engineeringEngineeringEnvironmental economicsConstruction engineeringGeographyPolitical scienceEconomicsMeteorology

Abstract

fetched live from OpenAlex

In Canada, off-site construction is still the exception rather than the norm when it comes to wood construction. In Europe’s Alpine Region or Scandinavian countries, off-site construction is standard when it comes to wood construction. This paper will focus on the reasons why Canada’s wood construction industry will shift from mainly on-site to mainly off-site construction over the next 10 to 15 years. In countries with relatively demanding requirements on energy efficiency and air tightness, off-site construction has been dominating the market for more than 20 years. British Columbia adopted the BC Energy Step Code in 2017, a roadmap defining the energy efficiency of buildings over the coming years leading up to 2032, when all new construction will be required to be Net Zero ready. It is expected that the National Building Code of Canada will also encourage higher energy performance levels in the near future. Consequently, thermally better-performing envelopes will have to be produced and rigorous air tightness levels will have to be achieved for the sustainability goals given by the province. Envelope assemblies will get thicker, bulkier and heavier to meet these requirements. In this regard, a market shift to a greater amount of off-site construction is likely to be experienced to meet these targets in a controlled environment. This study is exploring the direct and indirect connections between sustainability and energy efficiency requirements given by codes to technical and cost-efficient solutions offered by industry.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.552
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.005
GPT teacher head0.175
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 teacher head, not a consensus.

Study designBench or experimental
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

Citations1
Published2019
Admission routes3
Has abstractyes

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