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Record W3022935980 · doi:10.3992/1943-4618.15.1.185

MOHAWK COLLEGE'S NET ZERO ENERGY AND ZERO CARBON BUILDING—A LIVING LAB FOR HIGH EFFICIENCY AND RENEWABLE ENERGY TECHNOLOGIES IN BUILDINGS

2020· article· en· W3022935980 on OpenAlexaboutno aff
Rutul Bhavsar, Anthony Cupido, Mariano Arriaga

Bibliographic record

VenueJournal of Green Building · 2020
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsnot available
Fundersnot available
KeywordsZero-energy buildingRenewable energyGreenhouse gasArchitectural engineeringEfficient energy useEnergy engineeringZero emissionGeneral partnershipEngineeringEnvironmental economicsEnvironmental scienceCivil engineeringBusinessWaste managementEconomics

Abstract

fetched live from OpenAlex

INTRODUCTION In recent years, large high efficiency and Net-Zero Energy Buildings (NZEB) are becoming a reality that are setting construction and energy benchmarks for the industry. As part of this significant effort, in 2018, Mohawk College opened the 8,981 m2 (96,670 ft2) Joyce Centre for Partnership and Innovation (JCPI) building in Hamilton, Ontario; becoming Canada's largest NZEB and zero-carbon institutional facility. The building integrated a high-efficiency design, construction materials, and technologies; as well as renewable energy technologies to significantly reduce its annual energy consumption and greenhouse gas emissions. Furthermore, the JCPI building was also designed as a living lab where students, faculty, researchers and industry are able to monitor and validate the performance of this state-of-the-art facility. The building was designed to have an energy use intensity of 73 kWh/m2·year (0.26 GJ/m2·year); hence, potentially consuming approximately 80% less energy than the average educational service building in Ontario. This paper gives an overview of the design criteria and technologies that were considered to achieve this innovative building.

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)0.001
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.025
Threshold uncertainty score0.083

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0020.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0250.003

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 head0.007
GPT teacher head0.190
Teacher spread0.183 · 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
GenreOther

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

Citations9
Published2020
Admission routes1
Has abstractyes

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