Impacts of Sustainable Transportation on the Development of Historic Cities: A Case Study of the Historic City of Mosul
Bibliographic record
Abstract
The historic centers of cities have shifted during the last period into economic and commercial centers; this change has made them lose their distinct urban identity since these commercial centers need a flow of traffic, and these fabrics cannot absorb such an intensity of traffic.The objective of the research is to assess the possibility of possessing the historic urban fabric of the city of Mosul with the capabilities and urban features to accommodate sustainable transportation systems within, reduce dependence on individual vehicles, and give the fabric capabilities for preservation and development.The study uses an analytical comparison of international sustainable transportation evaluation systems to identify the most vital indicators: accessibility, permeability, and internal connectivity.The spatial structure of Mosul's historic city center is analyzed using space syntax theory, UCL Depthmap 10, AutoCAD 2016, and ArcMap 10.8 to evaluate how it performs on these indicators.The results showed a high internal connectivity values for the fabric reaching 344 intersections/km² , with high integration values for the main circulation axes reaching (1.89) and their local control values reaching (2), with high coverage rates for service as crossing axes for the fabric reaching (83%).In conclusion, the study concluded that the historical urban fabric of the city of Mosul possesses the necessary urban structure and features that qualify it for sustainable transportation systems to work effectively within it.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".