Summer outdoor thermal risk area mapping on a university campus in Auckland, New Zealand
Bibliographic record
Abstract
Outdoor thermal risks in urban areas are increasingly critical due to climate change and urbanization. This study identifies high-risk areas at Auckland University of Technology, New Zealand, using a multi-layered approach integrating hazard, exposure, and vulnerability. Locations with Physiologically Equivalent Temperature (PET) exceeding 23°C were analyzed alongside user density and survey-based vulnerability assessments, pinpointing two high-risk zones. Future projections for 2050 and 2080 (RCP 4.5 and RCP 8.5 scenarios) indicate rising PET levels, amplifying thermal discomfort. Mitigation strategies, including green walls and tree planting, demonstrated PET reductions of 2°C and 3°C, respectively, under current conditions. These findings underscore the critical role of greenery in enhancing outdoor thermal comfort and resilience. The study’s replicable methodology offers urban planners a practical framework for addressing thermal risks and adapting outdoor spaces to climate change impacts, fostering urban livability.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".