Habitant’s Empowerment of urban timeworn textures along with improvement and renovation process: (Case sample: Qal’eh quarter of Dezful)
Bibliographic record
Abstract
Abstract. Today, urban timeworn textures are of the most important problems which cities are facing with. These textures are mainly parts of the city which are separated from evolutionary cycle and are formed as center of difficulties and inadequacies. These parts have lost livability during time and changing space patterns of construction and have many problems in terms of skeletal conditions, traffic, economic and social for modern life.Dezful is one of the cities suffering from timeworn textures among quarters of the city. We can point to Qal’eh quarter which is one of the oldest quarters of Dezful. Therefore, aim of this study is to recognize problems of timeworn and proposing appropriate solutions to empower habitants of this texture in order to renovation and improvement. Method of research is descriptive, analytical and surgery with a theoretical–participatory procedure. Data collecting method is in the form of library field and questionnaire about studied quarter it is dealt with feasibility of participation in improvement of timeworn texture of the quarter using supervisor of family questionnaire and some strategies were extracted to propose solution for improving and renovating this quarter.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".