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Record W3046354089 · doi:10.24891/fc.26.7.1469

On strategy for the development of multifunctional social infrastructure complexes in the ‘Smart City’ paradigm

2020· article· en· W3046354089 on OpenAlexaboutno aff
Anna L. SABININA, V.V. Sokolovskii, N.A. Shul'zhenko, N.A. Sychova

Bibliographic record

VenueFinance and Credit · 2020
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Industrial Development
Canadian institutionsnot available
Fundersnot available
KeywordsProject commissioningQuarter (Canadian coin)Space (punctuation)Computer scienceBalance (ability)Operations researchSupply and demandRisk analysis (engineering)BusinessEngineeringPublishingEconomicsGeographyMedicine

Abstract

fetched live from OpenAlex

Subject. The article describes the findings of the authors of fundamental strategic decisions on the formation of multifunctional urban complexes, using the housing demand and supply criterion. Objectives. We undertake a comprehensive study aimed at perfecting the methodology for evaluating the options for city infrastructure development at two stages, i.e. strategic, when general targets of feasible commissioning are determined, and current, when parameters of demand for facilities are taken into account. Methods. The study employs methods of expert survey, statistical data processing, predictive and investigative analysis. Results. We explored factors of creating amenities and comfort in residential construction areas, developed an algorithm to calculate the volume of new living space commissioning on the basis of evaluating demands in the Smart City paradigm. Conclusions. The study shows the cost increase depending on the built-up area, number of floors, and the balance between the type of capacity and the number of residents in the quarter (linear relationship).

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.004
Scholarly communication0.0040.003
Open science0.0010.001
Research integrity0.0020.001
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 head0.108
GPT teacher head0.247
Teacher spread0.139 · 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 designTheoretical or conceptual
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
Published2020
Admission routes1
Has abstractyes

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