Bibliographic record
Abstract
Countries around the world have responded to growing concern about the problems associated with sprawling development patterns by creating a wide range of policy instruments designed to manage urban growth and protect open space. Greenbelt policy is one of the most effective measures against the current environmental problems and nature conservation issues. As it provides an important protection against urban sprawl, providing a ‘green lung’ around towns and cities. The creation of sustainable greenbelts is an integral part of sustainable urban design in a community and regional context. The goal of this sustainable greenbelt is through the design process, to reduce the use of non – renewable resources, minimize the negative environmental impacts, engage the users with the natural environment and provides many more opportunities for recreation, alternative and safer transportation routes and wildlife habitat. From this point of view, This paper focuses on two key issues; firstly: study and analysis of the sustainable greenbelt around towns, which can help to make a difference both the community and the city, provide a greenbelt that not only provides additional open space but does so in a more sustainable manner requiring fewer non –renewable and resources ,secondly: assessing and analyzing the the greenbelt typologies in Vitoria Gasteiz - Spain (California) and Ontario (Canada) to find out extent of Sustainable current greenbelt design, in order to get greener greenbelt in the future follow the highest standards of sustainable development.
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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.004 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".