Enhancing Outdoor Thermal Comfort in Residential Areas of Arid Regions: A Case Study from Baghdad
Bibliographic record
Abstract
Residential areas significantly contribute to the increase in energy consumption necessary to meet cooling requirements for occupants' comfort.Enhancing human thermal comfort in outdoor environments is a crucial goal in achieving effective designs for open spaces.This study specifically surveys potential measures to enhance pedestrian thermal comfort in hot regions, addressing the issue of modern urban architecture's inability to adequately adapt to human thermal comfort and energy efficiency.It aims to propose different environmental treatments for open spaces between buildings and study their effect on improving pedestrian thermal comfort.For instance, the study employs cool pavements, vegetation, and water bodies.It conducted the evaluation in Baghdad during the hottest days of July, examining thermal comfort metrics using ENVI-met software.The study measures outdoor thermal comfort for six scenarios sequentially using the physiological equivalent temperature (PET).The results demonstrated the importance of environmental treatments for open spaces in residential complexes, and the analysis showed that vegetation has a strong effect on improving outdoor thermal comfort, followed by water bodies and finally paving and coating materials.
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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 | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".