On the master plan conformance with urban reality: A comparative assessment
Bibliographic record
Abstract
BACKGROUND AND OBJECTIVES: The gap between urban planning and its implementation in cities has led to the evaluation of urban plans which heightens the efficiency of plans. This research evaluates the dissimilarities between the city’s reality and planned prospects.METHODS: To assess that, the Delphi technique was utilized to determine the criteria then Geographic Information System and quantitative models namely Mean Center, Standard Deviational Ellipse, and Planning Implementation Rate were employed.FINDINGS: The outcomes reveal that Mashhad’s direction of urban development corresponds to the master plan. The second estimated alternative for the population (with 83.52%) has a high level of conformity. On the subject of land use, conforming and non-conforming uses account for 47% and 23.80% respectively. A preponderance of non-conforming uses is in the south-to-east, north, and northwest parts of the city, and zone 7 accommodates the highest area of non-conforming uses among other zones. The implementation rate is 94.7%, showing that the current urban forms were implemented following the master plan to a large extent. However, the construction outside the city’s limit is not under regulation. Three areas with high density located in the west, northwest, and east (Bahonar town) have the highest level of non-conformity.CONCLUSION: The master plan could not achieve its street network goal due to an approximately 58% mismatch with the existing network. As a result, the conflicts in spatial findings could have been shaped by the implementation or inattention to planning regulations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.039 | 0.058 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".