Outdoor Thermal Comfort Analysis in a Cold Continental Climate: The Case of a Pedestrian-Only Street in Downtown Toronto
Bibliographic record
Abstract
Increased interest in urban thermal comfort has emerged in recent years with unpredictable weather patterns and unprecedented temperature extremes around the world. Urban modelling computer software can help with understanding interactions between built environment and microclimates. However, results of simulations can be difficult to interpret if acceptable thermal conditions for a location are unknown. Using a compound approach of field investigation and microclimate modelling for a pedestrian-only street in Toronto, Canada, this study investigates urban outdoor thermal comfort (OTC) in a cold continental climate. Four thermal indices were used to analyze field data and the results were compared with OTC research conducted in other climates. In this study, the Physiological Equivalent Temperature (PET) provided the strongest annual correlation with the pedestrian thermal sensation votes. A PET comfort range between 9°C and 24°C was found. Survey results were then used to interpret the simulated effect of urban vegetation within the case study microclimate during a summer scenario.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".