Sustainable urban development of mobility and streetscape in historic city quarters, an ancient street in Alexandria - Egypt, as a case study
Bibliographic record
Abstract
A historic urban district is a quarter built many years ago and contains valuable memories over a limited area with narrow streets for pedestrians, primitive transportation, and outdoor activities. Over the years, many districts have been growing randomly, and motorized transport has enlarged significantly and created severe problems. Improving the situation needs heritage protection and sustainable mobility development on its streets. The desired mobility focuses on managing travel demands, accessibility for all street users, and enhancing the environment. This research presents a proposed approach with an application framework for sustainable mobility development on historic roads according to its current conditions at the strategic level. It includes sequential phases to define desired goals, formulate and evaluate planning scenarios containing different action measures based on sustainability indicators and application of micro-simulation. In case of inappropriate evaluation results, approach phases allow the modification and re-evaluation of additional measures until deciding an acceptable solution. The application is limited to Ras El-Teen Palace Street, prominent in the ancient El Gomrok district, Alexandria and restricted to a Do-Nothing solution and a planning scenario. The application proves the approach's practicality and feasibility by improving traffic behaviour. Furthermore, the planning approach can indicate technical recommendations for further improvement.
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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 | 0.002 |
| Science and technology studies | 0.001 | 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".