Park cool island modifications to assess radiative cooling of a tropical urban park
Bibliographic record
Abstract
Many cities experience urban overheating from climate change and the urban heat island phenomenon. Previous studies demonstrate that parks are a potential nature-based solution to mitigate urban overheating through the ‘Park Cool Island’ (PCI) effect. PCI intensity can be measured through field measurements (FM) or remote sensing. This FM study used a network of meteorological sensors within a park and in its surrounding urban area to ascertain its PCI intensity in Singapore from January to December 2022. Consistently cooler air temperatures were found throughout a 24-h period in the park area, with mean daytime (nighttime) PCI intensity measured ~ 2.21 °C (~ 1.69 °C). A modified version of PCI (PCI modified ) was developed to highlight the radiative cooling differences between the urban and park areas. PCI modified leverages on the network of sensors to preserve the spatial granularity of data, allowing for the interpolation of point data across the study area. By employing Geographical Information Science concepts, the model visualises the diurnal changes in PCI modified intensities with respect to tree height, tree density, and building height; significant cooling is positively (negatively) correlated with tree height and density (building height). This study demonstrates a comprehensive analysis of PCI and cooling intensities of parks using FM in understudied tropical urban environments.
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How this classification was reachedexpand
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 | 0.001 | 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 | 0.000 | 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) | 0.000 | 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 teacher head, 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".