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Record W3133823173 · doi:10.17673/vestnik.2020.04.14

REVITALIZATION OF THE HISTORICAL QUARTER. EXPERIENCE IN APPLYING THE CONTEXTUAL APPROACH

2021· article· en· W3133823173 on OpenAlexaboutno aff
N. A. Orlova, Dmitry Nikolaevich Orlov, Anastasia A. GARSHINA

Bibliographic record

VenueGradostroitelʹstvo i arhitektura · 2021
Typearticle
Languageen
FieldEngineering
TopicConstruction Management and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)ArchitectureOrder (exchange)Center (category theory)Urban planningSamaraEnvironmental planningArchitectural engineeringOperations researchComputer scienceHistoryOperations managementGeographyCivil engineeringEngineeringBusinessArchaeology

Abstract

fetched live from OpenAlex

For the Samara architecture of our time, the urgency and priority of the problem of preserving and developing the historical center is obvious. This study is at the forefront of the current controversy on this issue and gives its own version of the solution to the problems. The practical signifi cance of the research is a new articulated and visualized experience of reconstructive actions in the historical environment. The method of urban planning analysis of the site in order to identify the reserves of the territory is proposed. Methods of working with the architectural form necessary for preserving the morphotype of the old city in the conditions of modern development are shown. Conclusions and recommendations based on specifi c urban planning material 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)0.003
metaresearch head score (Gemma)0.004
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 score0.010
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.017
Scholarly communication0.0060.004
Open science0.0010.005
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0100.001

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 head0.015
GPT teacher head0.209
Teacher spread0.194 · 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

Citations9
Published2021
Admission routes1
Has abstractyes

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