Understanding the urban heat island in Montreal, Quebec through local climate zone classification and crowd sourced demographic data
Bibliographic record
Abstract
The Urban Heat Island (UHI) effect occurs when urbanized areas are warmer than less urbanized areas. In Montreal, Quebec, the phenomenon is not commonly studied through the air temperature felt by residents. Therefore, I aim to understand the UHI phenomenon in Montreal through a Local Climate Zone (LCZ) classification of the city and through crowdsourced air temperature datasets. The LCZ classification system was developed specifically to study the UHI effect in urban environments. I used Geographic Information System (GIS) methods, spatial data, and air temperature datasets from Netatmo weather stations and federal weather stations. My results show that the highest average air temperature can be found in areas classified as LCZ 3 – Compact low-rise. Additionally, there is significant difference in air temperature between “compact” zones and “open” zones. Further research relying on air temperature will require more weather stations across the City of Montreal and updated spatial data
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".