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Record W2265144199

Управление и прогнозирование развития малоэтажной жилой застройки на городской и пригородной территории

2014· article· ru· W2265144199 on OpenAlexaboutno aff
Т В Учинина, Ю В Кваша

Bibliographic record

VenueСовременные проблемы науки и образования · 2014
Typearticle
Languageru
FieldSocial Sciences
TopicRegional Socio-Economic Development Trends
Canadian institutionsnot available
Fundersnot available
KeywordsInvestment (military)AttractivenessPosition (finance)General partnershipBusinessAffordable housingEconomic growthPolitical scienceFinanceEconomics
DOInot available

Abstract

fetched live from OpenAlex

In recent years, the construction of low-rise housing is the most promising and growing field of housing policy in the Russian Federation. Housing choice from a position of consumers is based on three main positions: housing must be affordable, comfortable, environmentally friendly. The article presents an analysis of the experience of low-rise construction in the United States, Canada, Germany; retrospective analysis of input residential buildings in Russia and Penza region. The analysis of the attractiveness of suburban areas for organized low-rise building on two areas: Bessonovskiy and Penzenskiy, and also for the city of Penza. Identified problems that may be encountered in the process of low-rise buildings and the proposed solutions, in particular highlighted the need to develop proposals to attract private investment to create them in a publicprivate partnership.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.012
Threshold uncertainty score0.041

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.002
Scholarly communication0.0030.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0120.004

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 head0.022
GPT teacher head0.279
Teacher spread0.257 · 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 designNot applicable
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
Published2014
Admission routes1
Has abstractyes

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