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Record W4410129626 · doi:10.3390/buildings15091562

Evaluating the Urban Heat Island Effect in Montreal: Urban Density, Vegetation, Demographic, and Thermal Landscape Analysis

2025· article· en· W4410129626 on OpenAlexaffabout
Yassine Hedeya, Abdelatif Merabtine, Wahid Maref

Bibliographic record

VenueBuildings · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicUrban Heat Island Mitigation
Canadian institutionsÉcole de Technologie SupérieureUniversité du Québec à Montréal
Fundersnot available
KeywordsUrban heat islandVegetation (pathology)GeographyUrban landscapeEnvironmental sciencePhysical geographyMeteorologyEnvironmental planning

Abstract

fetched live from OpenAlex

Montreal experiences a significant urban heat island (UHI) effect, potentially intensified by its dense urban structure, varied vegetation, and demographic distribution, leading to substantial outdoor thermal discomfort, especially during heatwaves. To quantify this, measured thermal landscape data were analyzed over several months in Montreal, including heatwave periods, and outdoor thermal comfort was assessed using the humidex, discomfort index, heat index, and temperature–humidity index. The results indicated notable temperature and humidity variations across the city, with the exceedance of thermal comfort index thresholds being significantly higher during heatwaves (humidex: 10.83%, discomfort index: 53.33%, heat index: 24.77%, temperature–humidity index: 36.67%) compared to normal periods. This study provides a quantitative evaluation of UHI-induced outdoor thermal discomfort in Montreal, emphasizing its severity during heatwaves and analyzing the influence of urban density, vegetation, and anthropogenic emissions, thus offering valuable insights for urban planning strategies to mitigate public health impacts.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.430

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 communication0.0000.000
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 head0.007
GPT teacher head0.253
Teacher spread0.246 · 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 designObservational
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

Citations5
Published2025
Admission routes2
Has abstractyes

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