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Identity building in contemporary urban architecture (on the example of Irkutsk)

2022· article· en· W4313028385 on OpenAlexaboutno aff
Konstantin Kolodin, P. A. Vinokurova

Bibliographic record

VenueIzvestiya vuzov Investitsii Stroitelstvo Nedvizhimost · 2022
Typearticle
Languageen
FieldEngineering
TopicConstruction Management and Sustainability
Canadian institutionsnot available
Fundersnot available
KeywordsArchitectureIdentity (music)Context (archaeology)Urban planningQuarter (Canadian coin)Architectural engineeringUrban structureWork (physics)Civil engineeringPlace identityResidential areaEnvironmental planningRegional scienceGeographySociologyArchaeologyAestheticsEngineeringArt

Abstract

fetched live from OpenAlex

In this work, a concept of modern residential development, including public infrastructure, integrated seamlessly into the historic centre of Irkutsk was elaborated. The proposed location of the quarter lies within the boundaries of Rabochaya Street, the territory of the Machine-Building Plant, the Ushakovka river embankment and Frank Kamenetsky and Oktyabrskaya Revolution streets. The contemporary town planning structures within the historical context were analysed using the examples of various cities. The components of urban identity and trends, which affect its formation, were studied. The characteristics of the form making for the objects having different purposes within the urban structure of Irkutsk were defined. Design solutions for constructing a modern residential area together with public buildings in the historic centre of Irkutsk were provided. When developing the project, studying urban identity and its implementation in the design solutions was emphasised. The proposed concept aims to preserve urban identity and stresses the characteristics of the historic architecture of the city in current urban development.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.009
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0050.012
Scholarly communication0.0040.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.031
GPT teacher head0.229
Teacher spread0.199 · 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 designQualitative
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".

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Citations0
Published2022
Admission routes1
Has abstractyes

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