Suitability of Green City Criteria (LEED) According to the Egyptian Special Environmental Characteristics
Bibliographic record
Abstract
The research aims to suit the criteria for classifying green cities according to the characteristics of the Egyptian environmental zones to select the most relevant zone for sustainable green cities. The Egyptian cities consume large quantities of materials, energy, and water causing different problems facing cities and their population. The criteria of sustainable green cities should be done according to the various characteristics of environmental zones in Egypt. The leadership in energy and environmental design (LEED) criteria for the Egyptian cities and communities’ system is selected according to the characteristics of environmental zones in Egypt, aiming to select the most relevant zones to construct sustainable green cities. According to the ecological, geographical, economic, political, social, historical, urban, and cultural characteristics of environmental zones that are different from one zone to another in Egypt, the influencing factors in the classification criteria are introduced to show the incentives, capabilities, and challenges facing cities in making green and sustainable transformation by using weighited overlay model in Arc GIS. By using the suitability scoring system, the most suitable environmental zone, namely the dry coastal zone, has the motivation and ability to transform the city into a green and sustainable city according to its particular environmental characteristics.
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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 | 0.000 |
| 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".