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Record W4389883762 · doi:10.1080/19401493.2023.2290103

Comparing overheating risk and mitigation strategies for two Canadian schools by using building simulation calibrated with measured data

2023· article· en· W4389883762 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueJournal of Building Performance Simulation · 2023
Typearticle
Languageen
FieldEngineering
TopicBuilding Energy and Comfort Optimization
Canadian institutionsConcordia UniversityUniversité de Sherbrooke
Fundersnot available
KeywordsOverheating (electricity)Environmental scienceBuilding envelopeThermal comfortRoofMeteorologyThermalEngineeringCivil engineeringGeography

Abstract

fetched live from OpenAlex

This paper compares the indoor overheating risk of two schools by considering the effect of selected building parameters, under extreme current and future climates, and proposes mitigation strategies. The indoor air temperature measurements were conducted in seven classrooms in two schools constructed in 1960 and 1990. These measurements are used to calibrate the building simulation models of these schools. The study's results show that, in the current extreme year, classrooms on upper floors with larger window-wall ratios WWR (60%) and lower thermal building envelope properties are at a higher risk of overheating. Conversely, in classrooms located on lower floors, or featuring a small WWR (10%), or better thermal properties, no other Climate-resilient measures are needed. Under extreme future years the external roller blind shading, night cooling, and cool roof measures will be necessary for both schools, particularly for last-floor classrooms with south orientation and a 60% WWR in 1960 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.

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 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 score0.355
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.003
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 head0.042
GPT teacher head0.285
Teacher spread0.243 · 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