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Justification of the Principles of Revitalization of the Built-up Territories for Sustainable Development of the Urban Environment

2020· article· en· W3009275484 on OpenAlexaboutno aff
A A Tyuterev, Olga Sotnikova, Ekaterina Prokshits

Bibliographic record

VenueIOP Conference Series Materials Science and Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicUrban Design and Spatial Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsSustainable developmentQuarter (Canadian coin)DemolitionUrban planningEnvironmental planningGentrificationStock (firearms)Position (finance)Urban regenerationBusinessRegional scienceEconomic growthPolitical scienceGeographyCivil engineeringEngineeringEconomicsFinance

Abstract

fetched live from OpenAlex

Abstract The analysis and justification of the basic principles of revitalization of the urban inhabited environment from position of sustainable development of territories. Are analyzed experience of gentrification in the USA and also the European countries; the program of renovation of housing in Moscow developed by the Government of Moscow and directed to resettlement and demolition of old low housing stock. The main shortcomings of such planning approaches are revealed. The step-by-step scheme of renovation of the residential quarter on the example of Voronezh is developed. Recommendations about change of planning structure of the reconstructed quarter taking into account the principles of sustainable development of the urban environment are formulated.

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 imitation

Not 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.

metaresearch head score (Codex)0.006
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.033

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.014
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.001

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.

Opus teacher head0.021
GPT teacher head0.185
Teacher spread0.164 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2020
Admission routes1
Has abstractyes

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