Survey management solutions of urban effete fabrics and exhibition optimal pattern in intervention (Case study: Quarter of Sartapole in Sanandaj city)
Bibliographic record
Abstract
Attention to urban old and effete fabrics as fabrics that have problem, not just in Iran but in the world has a long history. Organizing and improving this fabrics that more located in center and core of historical city, the best way to describe history and national identity and is one of bases for realization ideals innate development. The GIS based on functions, applied algorithms and their ability can as efficient tool helped management of effete fabrics in order to overcome said concerns. Present research has be done based analytical-descriptive method and with emphasis on practical aspects and with use of data collected at database of geographic information systems relevant to Sanandaj municipal. Case study is Sartapole quarter in Sanandaj city, this region selected because including effete indicator factors. In order to obtain to each of optimal patterns of management effete fabrics in case study including improvements, renovations, reformation,… based key indicators in identify exhaustion type of urban effete fabrics created multiple data layers such as: prices maps of blocks, maps of old buildings, Access Map, map of the number of classes, slope map of streets, landuse map, area map of blocks in case study, covering maps of roads, map of type materials and ... Finally, with spatial analysis and using practical algorithm in GIS and and usage of Fuzzy Logic were identified priority areas for the development of effete fabric based proposed solutions improvements, renovations, reformation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".