Are Historical Buildings More Adaptive to Minimize the Risks of Airborne Transmission of Viruses and Public Health? A Study of the Hazzazi House in Jeddah (Saudi Arabia)
Bibliographic record
Abstract
The coronavirus (COVID-19) pandemic has brought immense challenges to the natural and built environment to develop an antivirus-enabled model for reducing potential risks of spreading the virus at varied scales such as buildings, neighborhoods, and cities. Spatial configurations of structures may hinder or assist the spread of viruses in the built environment. In this study, we have hypothesized that suitable air ventilation in historic buildings may enhance the built environment to combat the spreading of infectious viruses. To provide such quantitative shreds of evidence, we have generated and estimated an integrated model to summarize obtained information by considering natural ventilation, wind speed, inflow and outflow, wind direction, and forecasting the associated risks of airborne disease transmission in a historical building (i.e., the Hazzazi House in particular). Intrinsically, the results have demonstrated that the effectiveness of natural ventilation has directly influenced reducing the risks of transmitting airborne infectious viruses for the selected heritage building in Jeddah (Saudi Arabia). The adopted methods in this research may be useful to understand the potentials of conserving old heritage buildings. Consequently, the results demonstrate that natural air ventilation systems are critical to combat the spread of infectious diseases in the pandemic.
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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 | 0.002 | 0.001 |
| 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) | 0.000 | 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".