METHODS OF RENOVATION OF LOW-RISE RESIDENTIAL DEVELOPMENTS IN CONNECTION WITH LANDSCAPE RECULTIVATION (ON THE EXAMPLE OF ROSTOV REGION)
Bibliographic record
Abstract
One of major factors of deterioration in a microclimate of urban development in the conditions of the Rostov region, is degradation of landscapes owing to violation of water balance of the territory. In article the main reasons for violation of water balance which included natural features of the region, a consequence of anthropogenic influence, climatic changes, etc. are considered. Examples from the world practice of urban planning, which show the relevance and effectiveness of compensation for the effects of anthropogenic im-pacts and climate change using planning methods, are given. The experience of the United States, the Nether-lands, Canada and other countries that use water-saving technologies in planning is considered. The rela-tionship of urban planning and the formation of sustainable urban landscapes is shown. The integration of water-saving technologies into the urban environment can be a means of optimizing landscapes and a means of creating unique urban spaces. Reclamation of the urban landscape of low-rise buildings is a necessary step in creating a modern and comfortable urban environment in the conditions of the Rostov region. Meth-ods are proposed to compensate for negative changes in urban landscapes that can be applied at the stage of urban planning. As well as the proposed methods can be applied in the reconstruction of urban low-rise buildings. The considered methods concern not only urban landscapes, but also agricultural landscapes that surround small and medium-sized cities of the Rostov region. In article the author's concept of the organiza-tion of the low housing estate on a basis Urban- facies is submitted. Planning methods of regulation of water balance of the territory on the basis of models the ecological protective of landscapes are offered: an ecolog-ical core, an ecological corridor and an ecological barrier and also analogs from town-planning practice are considered. The reclamation of urban landscapes based on urban planning methods for regulating the water balance of the territory will allow creating unique urban spaces that are resistant to local climatic conditions and the possible consequences of climate change.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".