MétaCan
Menu
Back to cohort
Record W4234595365 · doi:10.32920/ryerson.14665998

Least cost analysis for Canadian new housing : identifying the most cost-effective specifications to achieve improved energy efficiency standards

2021· preprint· en· W4234595365 on OpenAlexaffabout
Aya Dembo

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsUpgradeGreenhouse gasEfficient energy useTariffBuilding envelopeEnvironmental economicsProfit (economics)Photovoltaic systemEngineeringReliability engineeringEnvironmental scienceArchitectural engineeringComputer scienceBusinessThermalEconomicsElectrical engineering

Abstract

fetched live from OpenAlex

This thesis presents the methodology developed to identify the most cost-effective specifications that could be applied to the currently practiced new housing constructions in Canada to achieve improved energy efficiency standards, while maintaining an adequate level of thermal comfort. The results showed that, based on the life cycle cost analysis of 30 years, the optimal solutions (or upgrades) comprised of improvement in the thermal resistance of the building envelope, and installation of the most efficient heating, ventilating, and air-conditioning systems, resulting in up to 31% reductions in the estimated annual energy consumption and the greenhouse gas emissions, while achieving an EnerGuide Rating of 8, thereby meeting the new requirements of the upcoming 2012 Ontario Building Code. With the installation of a residential photovoltaic system, the estimated profit of up to $89,035 could be achieved through Ontario's micro Feed-in-Tariff (FIT) program, allowing a homeowner to pay for the implementation of additional upgrade(s).

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.986
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
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 head0.032
GPT teacher head0.290
Teacher spread0.258 · 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 designSimulation or modeling
Domainnot available
GenreMethods

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

Citations4
Published2021
Admission routes2
Has abstractyes

Explore more

Same topicSustainable Building Design and AssessmentFrench-language works237,207