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Record W6912718422 · doi:10.5281/zenodo.6907567

RECOMMENDATIONS FOR THE IMPLEMENTATION OF THE PRINCIPLES OF ECO-CITIES IN THE URBAN AREAS OF BISHKEK

2022· article· en· W6912718422 on OpenAlexaboutno aff

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2022
Typearticle
Languageen
FieldEngineering
TopicSustainable Building Design and Assessment
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Investment (military)Plan (archaeology)Urban planningLegislatureRelevance (law)Stove

Abstract

fetched live from OpenAlex

The relevance of introducing the principles of an eco-city in the urban areas of Bishkek is due to the deterioration of the environmental performance of the city, where the main reason is the instability of the entire territory management system. The purpose of the article is to give recommendations on the implementation of the principles of the eco-city in the urban environment. Recommendations were made: 1. To improve the ecology of Bishkek, it is necessary to reduce the existing ratio of private housing (approximately 65x35) to high-rise buildings, switch to alternative energy sources, and reduce heat losses. The ratio of 65x35 actually coincides with the ratio of the stove and central heating. 2. For institutional and legislative improvement of the level, a pilot project of the "green" quarter is needed. We propose to create such a project as social housing with green infrastructure; 3. It is profitable to build a new spot development with off-grid connections, which unloads old engineering networks due to alternative energy, heat and light. With the deterioration of engineering and technical infrastructure by 90%, this initiative is relevant; 4. Living roofs, vertical gardening, green technologies are easiest to implement in commercial, public buildings; 5. The creation of a master plan for an eco-digital city remains relevant; 6. Ultra-modern "green" quarter - an investment opportunity as a point of growth.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.436
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.044
GPT teacher head0.272
Teacher spread0.228 · 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 teacher head, not a consensus.

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

Citations0
Published2022
Admission routes1
Has abstractyes

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