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Record W4400963000 · doi:10.34925/eip.2023.153.4.221

ECONOMIC JUSTIFICATION FOR RENOVATION SERVICES OF A TYPICAL QUARTER

2023· article· ru· W4400963000 on OpenAlexaboutno aff
Е.В. ИЛЬИНА, Anna Romanova, С.Ф. ФЕДОРОВА, Л.Б. МАМЕДОВА, В.Р. МУРАТДИНОВА

Bibliographic record

VenueЭкономика и предпринимательство · 2023
Typearticle
Languageru
FieldEngineering
TopicBIM and Construction Integration
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Architectural engineeringBusinessEngineeringHistoryArchaeology

Abstract

fetched live from OpenAlex

Важной частью разрешения проблем, связанных с реновацией выступает разработка и внедрение эффективного механизма как планирования, так и финансирования, посредством которого все мероприятия и будут осуществляться. Для определения целесообразности введения реновации в регионе проведен критический анализ жилого фонда и отдельно произведен расчет примерной общей площади хрущевок, годы строительства которых находятся во временных рамках с конца 1950-х по 1972 г. с учетом деления по районам. В результате, которого общая площадь составила примерно 3866388,08 кв. м. В городе представлены многоквартирные дома разных серий построек включая большое количество кирпичных домов. Показано, что программа должна быть направлена, в первую очередь, на панельные «хрущевки» ранней постройки. An important part of resolving the problems associated with renovation is the development and implementation of an effective mechanism for both planning and financing, through which all activities will be carried out. To determine the feasibility of introducing renovation in the region, a critical analysis of the housing stock was carried out and a separate calculation was made of the approximate total area of Khrushchev houses, the years of construction of which are in the time frame from the late 1950s to 1972, taking into account the division by districts. As a result, the total area was approximately 3,866,388.08 sq. m. The city presents apartment buildings of different series of buildings, including a large number of brick houses. It is shown that the program should be directed, first of all, to panel "Khrushchev" houses of early construction.

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)0.007
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: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0040.002
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0150.001

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 head0.013
GPT teacher head0.237
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".

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Citations0
Published2023
Admission routes1
Has abstractyes

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