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ASSESSMENT OF THE SOCIAL INFRASTRUCTURE OF THE URBAN DEVELOPMENT POTENTIAL USING GIS-ANALYSIS ON THE EXAMPLE OF TOMSK

2019· article· en· W2990018121 on OpenAlex
Anastasia Moskovchenko, Mariya V. Kozina

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInterexpo GEO-Siberia · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicRegional Socio-Economic Development Trends
Canadian institutionsnot available
Fundersnot available
KeywordsGeographic information systemGeographyQuarter (Canadian coin)Resource (disambiguation)Plot (graphics)Environmental planningEnvironmental resource managementGIS DayGIS and public healthCartographyComputer scienceEnvironmental science

Abstract

fetched live from OpenAlex

This study presents the results of the application of information technology to assess the urban development potential of the territory on the example of the city of Tomsk. A two stages GIS analysis of the territory of a large administrative district of the city of Tomsk was carried out. At the first stage, an assessment was made of the needs of the territory of the Oktyabrsky District for social infrastructure facilities. The second step, based on the results of the assessment, was the procedure for finding a land plot for the construction of a general education institution (school) in the residential quarter. Information systems used to search for a land plot for school construction are described and analyzed. Prospects for the development of a GIS resource were identified, in which data on social infrastructure elements for the entire city of Tomsk and the Tomsk region will be combined in a map format using data from GIS analysis methods.

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.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.294
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
Bibliometrics0.0000.001
Science and technology studies0.0000.001
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 head0.029
GPT teacher head0.305
Teacher spread0.277 · 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