MétaCan
Menu
Back to cohort
Record W1947276255 · doi:10.1139/cjce-2015-0234

Reducing Ontario’s new single-family residential heating energy consumption by 80% by 2035: economic analysis of a tiered framework of performance targets

2015· article· en· W1947276255 on OpenAlexaffvenueabout
Amanda Yip, Russell Richman

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2015
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsBaseline (sea)Energy consumptionEnvironmental economicsConsumption (sociology)HVACWork (physics)Efficient energy useMainstreamCapital costArchitectural engineeringEngineeringEconomics

Abstract

fetched live from OpenAlex

Growing environmental consciousness and rising energy prices have emphasized the need for substantial energy savings in the single-family residential building sector. To achieve this, more stringent performance requirements are needed. The intent of this work is to develop a framework and preliminary policy implementation strategy to achieve an 80% reduction in heating energy consumption by 2035 for newly constructed single-family dwellings across Ontario (Canada). A tiered framework of heating energy consumption targets was developed using current (2012) Ontario building code requirements as the baseline and building enclosure/HVAC requirements estimated as necessary to achieve the Passive House Standard in Ontario’s two climate zones. An Ontario based large track homebuilder estimated construction capital costs for each tier to examine potential cost barriers against implementation. A significant cost premium of over $65 000 (CAD) (54%) exists between the baseline consumption and the overall 80% heating energy reduction target; a result of unfamiliarity and lack of experience designing and constructing to the proposed levels. This research concludes a large gap exists between early adopters and the mainstream construction industry in terms of super-insulated house construction.

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 score0.258
Threshold uncertainty score0.976

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.010
GPT teacher head0.176
Teacher spread0.166 · 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

Citations11
Published2015
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Civil EngineeringSame topicBuilding Energy and Comfort OptimizationFrench-language works237,207