MétaCan
Menu
Back to cohort
Record W2596610442

THE ROLE OF APPRAISAL SERVICES WHEN CARRYING OUT THE STATE CONTROL OVER THE USE OF LAND IN THE RUSSIAN FEDERATION

2016· article· en· W2596610442 on OpenAlexvenueno aff
Natalya Viktorovna Lutovinova, Alla Andreevna Neznamova, Georgij Nikolaevich Kuleshov, Viktor Anatolevich Bulaev, Denis Viktorovich Shmyrev

Bibliographic record

VenueThe Journal of Internet Banking and Commerce · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicLegal and Policy Issues
Canadian institutionsnot available
Fundersnot available
KeywordsCadastreControl (management)Land managementLegislationState (computer science)Russian federationValuation (finance)Land administrationLand information systemLand useComputer scienceEnvironmental resource managementEnvironmental planningBusinessLawPolitical scienceAccountingCivil engineeringEconomicsGeographyEngineering
DOInot available

Abstract

fetched live from OpenAlex

The issue of the state control over land usage in the Russian Federation arises particular interest and conflicting opinions in modern law science, since the land users cannot reasonably control their actions and voluntarily take appropriate measures for its improvement reasonably and to a sufficient degree, especially if it concerns their financial and material interests. From technical, organizational and material point of view the individual land users are not always able to provide organization of certain forms of modern control on their own. It is impossible to secure the unity of control actions, their coherence, analysis and assessment. The system of land management includes state cadastral valuation, land monitoring, state land control etc. The goal of state land control is to ensure that natural and legal entities as well as state officials adhered to the of land legislation aimed at the efficient usage and legal protection of land. The article analyses the procedures of state control over land usage in the Russian Federation.

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)0.009
metaresearch head score (Gemma)0.014
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 score0.050
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0090.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0050.003
Scholarly communication0.0080.003
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.029
GPT teacher head0.311
Teacher spread0.283 · 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

Citations2
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of Internet Banking and CommerceSame topicLegal and Policy IssuesFrench-language works237,207