Outdoor Thermal Comfort during Anomalous Heat at the 2015 Pan American Games in Toronto, Canada
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.
Bibliographic record
Abstract
Mass sporting events in the summertime are influenced by underlying weather patterns, with high temperatures posing a risk for spectators and athletes alike. To better understand weather variations in the Greater Toronto Area (GTA) during the Pan American Games in 2015 (PA15 Games), Environment and Climate Change Canada deployed a mesoscale monitoring network system of 53 weather stations. Spatial maps across the GTA demonstrate large variations by heat metric (e.g., maximum temperature, humidex, and wet bulb globe temperature), identifying Hamilton, Ontario as an area of elevated heat and humidity, and hence risk for heat-related illness. A case study of the Hamilton Soccer Center examined on-site thermal comfort during a heat event and PA15 Soccer Games, demonstrating that athletes and spectators were faced with thermal discomfort and a heightened risk of heat-related illness. Results are corroborated by First Aid and emergency response data during the events, as well as insight from personal experiences and Twitter feed. Integrating these results provides new information on potential benefits to society from utilizing mesonet systems during large-scale sporting events. Results further improve our understanding of intra-urban heat variability and heat-health burden. The benefits of utilizing more comprehensive modeling approaches for human heat stress that coincide with fine-scale weather information are discussed.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.012 | 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 it