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Record W3134323300 · doi:10.17673/vestnik.2020.04.12

NEW APPROACH TO THE COMPREHENSIVE RECONSTRUCTION OF HISTORICAL QUARTERS

2021· article· en· W3134323300 on OpenAlexaboutno aff
Tatiana V. VAVILONSKAYA, Yulia L. RAIKHEL

Bibliographic record

VenueGradostroitelʹstvo i arhitektura · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Socio-Economic Development Trends
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)ZoningBlock (permutation group theory)Computer scienceGeographyCivil engineeringArchaeologyEngineeringMathematics

Abstract

fetched live from OpenAlex

The article provides a retrospective analysis of existing approaches to the complex reconstruction of block buildings, which developed against the background of various scientifi c paradigms. Within the framework of the paradigm of territorial development management, a new investment and prognostic approach to the complex reconstruction of historical quarters is proposed on the example of Samara. The historic quarter is viewed as a planning module for the transformation processes of a sett lement. Reconstruction of the historical quarter is presented in the aggregate of problems of preserving and developing its buildings, providing residents with the necessary level of engineering, social and transport infrastructures. A method for calculating the rates of return for complex reconstruction is proposed, which serves to test the modes of the security zoning proposed for a historical sett lement. Particular att ention is paid to the preparation of initial data for calculating the rates of return for complex reconstruction for a number of quarters selected as reference.

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)0.002
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.022

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0080.007
Science and technology studies0.0010.003
Scholarly communication0.0040.004
Open science0.0010.002
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.046
GPT teacher head0.269
Teacher spread0.224 · 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

Citations12
Published2021
Admission routes1
Has abstractyes

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