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Record W3116218507 · doi:10.5430/ijfr.v12n1p71

Financial Tips on the Need to Identify Active Degassing Structures When Planning Territory Development Using the Functional Zoning Method

2020· article· en· W3116218507 on OpenAlexvenueno aff
Arina Vyacheslavovna Rudenko, В В Шаймарданова

Bibliographic record

VenueInternational Journal of Financial Research · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Sustainability and Technology
Canadian institutionsnot available
FundersKazan Federal University
KeywordsZoningDistribution (mathematics)GeographyBusinessEnvironmental planningEnvironmental resource managementPolitical scienceEnvironmental scienceLaw

Abstract

fetched live from OpenAlex

The article demonstrates financial instructions and ring degassing structures decoded by the author's technique in the northeast and southeast of Kazan. The structures of various types were identified in areas of the territories of the Volga and Soviet districts of the city and mapped on the functional zones of Kazan of these areas. Residential areas Nagorny, Aki, Quarry of the Sovetsky district, and Mirny, Ferma-2 of the Volga district of Kazan were selected as the research territories. This matter overly helps visually identify areas of the city that are in potential jeopardy of non-human impact. The article indicates the hypothesis about the need to consider the active structures of hydrogen degassing during the development of the territory from analyzing the functional zoning scheme of the studied territory, and provides a detailed comparative analysis of the distribution of ring structures in residential and green functional zones.

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 score0.010
Threshold uncertainty score0.035

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0100.001

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 head0.121
GPT teacher head0.409
Teacher spread0.288 · 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

Citations0
Published2020
Admission routes1
Has abstractyes

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