Rebuilding Ramadi in Concept of a Fractured City and Rules of Urban Coherence
Bibliographic record
Abstract
The suffering and trauma resulting from destruction of cities has generated an intense reaction to citizens, civil organizations and university gathered together and voluntarily to formulate general policies that can restore normal life to work in region and guide and guide reconstruction. Some may press for years for a particular city and regional improvements Such as mass transit, housing, public places, riverfront development, social and economic justice, as well as good urban design. The orientation and guidance of work and reliance on certain principles and rules requires representatives of city to adopt concepts that move from complexity to simplicity and looking for diversity and interdependence and organization within certain limits and hierarchical hierarchy achieves desired urban cohesion and destruction that city has opportunity to apply this within concepts are catalysts for process of interaction among different composites in city, it facilitates occurrence of any gathering can be system-wide. As for urban form, there are no stimulus parts, but every structure or component of urban form is working at least two other components. The various components are interconnected randomly to be integrated into final components of each organic freely interacting between different elements and components. The research deals with formulation of an indicative guide drawn from concept of fractal city and rules of urban cohesion in reconstruction of city of Ramadi "destructive" with community participation at all levels restore city's historical and cultural identity and other aspects that keep it as a living city as a functional, social, environmental and service.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.023 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".