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Record W2790813452 · doi:10.17673/vestnik.2017.01.16

ARCHITECTURE OF PUBLIC SHOPPING CENTERS IN THE HISTORICAL PART OF A CITY: KUBAN EXAMPLE

2017· article· en· W2790813452 on OpenAlexaboutno aff
Oleg S. Subbotin

Bibliographic record

VenueGradostroitelʹstvo i arhitektura · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicUrbanization and City Planning
Canadian institutionsnot available
Fundersnot available
KeywordsArchitectureQuarter (Canadian coin)Public spaceSpace (punctuation)Architectural engineeringAdaptation (eye)Work (physics)Urban planningCity environmentHistoryCivil engineeringGeographyEngineeringArchaeologyComputer scienceEnvironmental planningPsychology

Abstract

fetched live from OpenAlex

Analysis of construction of public shopping centers in the historical part of the city is presented. The main problems of the reconstruction of historical quarter architectural appearance are outlined. The historical quarters of Krasnodar are viewed. Special att ention is paid to restoration and adaptation of monuments for modern functions on the example of Kuban historical sett lements. The att ention is focused on the architectural plastic, shape and space of buildings and structures designed for specifi c purposes. The problem of modern functional and spatial development of the historic environment, taking into account space reorganization is revealed. The practical signifi - cance of this work can serve as a basis for effi cient architectural and planning organization of public shopping centers in the historical part of the city as at project level and in implementation of urban development programs.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.022
Threshold uncertainty score0.044

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0020.001
Scholarly communication0.0020.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0070.000

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.

Opus teacher head0.127
GPT teacher head0.304
Teacher spread0.176 · 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 designObservational
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

Citations1
Published2017
Admission routes1
Has abstractyes

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