Environmental Value of Housing Gardens in Urban Landscape: A Case Study of Tusba/Van Detached Home Gardens
Bibliographic record
Abstract
Residential gardens; increasing the quality of urban landscape by increasing the agricultural skills of the people of the city, providing economic gain, being one of the most effective methods of combating food, improving air quality, contributing to the reduction of CO2 emissions and temperature, enabling social activities, recreation and leisure time opportunities has positive effects. The detached house gardens in the city of Van are characterized by multifunctionality, which gives people different advantages as in other cities. The aim of this study is to determine the place, properties and importance of residential gardens in urban life in urban area. In the study, detached house gardens, which are important traditions, were found in the neighborhoods of Tusba in Van. The literature on the subject has been searched, geographic information system software has been used to determine the available area uses and on-site observation and analysis methods have been used. As a result, the neighborhood with the highest number of residences with gardens was identified as Altıntepe Quarter with 893 residences. At the end of the study, the aim of this study is to develop the suggestions for the sustainability of the garden culture by revealing the role of detached house gardens in the city which existed throughout history and whose examples are decreasing today. Keywords: Urban landscape, cultural heritage, detached house gardens, Tusba county. DOI: 10.7176/JSTR/6-01-07
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".