A seasonal assessment of urban outdoor thermal exposure in a humid continental climate using the MaRTy observational platform
Bibliographic record
Abstract
Many cities in the northern hemisphere experience both extreme heat and extreme cold weather. Pedestrians are exposed to these thermal extremes, causing bodily stress. With a growing and ageing urban population, city design that contributes to the mitigation of summer heat exposure while also reducing winter cold exposure is of increasing importance. Pedestrian thermal exposure depends on several microclimatic factors in addition to air temperature, including wind speed, humidity, as well as shortwave and longwave radiation, which can be quantified by the mean radiant temperature (Tmrt). There has been little study of the impacts on pedestrian thermal exposure in climates with high humidity during summer and snow cover in the winter. We gathered seasonal radiation data from varied urban microclimates using the six-directional Tmrt method in a Canadian city. We deployed a mobile human-biometeorological weather station (MaRTy cart), which has previously been used primarily in hot, dry climates. Tmrt profiles are decomposed into their directional components, and they demonstrate substantial differences in the drivers of thermal exposure between seasons and locations within the city.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".