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Record W4292588996 · doi:10.26565/2524-2547-2021-62-03

FORMATION OF PRODUCTION GROWTH POINTS ON THE BASIS OF MINERAL - RAW MATERIAL RESOURCES AS A FACTOR OF IMPROVEMENT OF THE TERRITORIAL STRUCTURE OF THE INDUSTRY OF THE REPUBLIC OF KARAKALPAKSTAN

2021· article· en· W4292588996 on OpenAlex

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

VenueSocial Economics · 2021
Typearticle
Languageen
FieldEngineering
TopicEngineering and Environmental Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPopulationNatural resourceCapitalizationBusinessNatural resource economicsEconomicsEconomy

Abstract

fetched live from OpenAlex

The use of mineral resources plays an important role in the global economy. “As noted in the British newspaper“ Financial Times ”, this sector ranks 1st in the world in terms of capitalization of the largest companies, including mining itself (excluding oil and gas) - 5th place among global industries after the banking sector, oil and gas industry, pharmaceutical and computer industries"(Kondratyev, 2014). In the developed and rapidly developing countries of the world, industrial growth is achieved through the effective use of the local potential of natural resources, improvement of the structural composition of the industry. According to the World Bank, in 2018 the share of mineral resources in GDP was 0,9 percent in Canada, 3,5 percent in Australia and 2,5 percent in Brazil, while in Uzbekistan the figure was 12,3 percent (Saydaxmedov, 2020). Many large scientific centers around the world are working on changing the methodology for the economic assessment of mineral resources, taking into account the regional economy, new economic geography, changes in the subjects of the institutional economy and the growth of knowledge that has occurred in recent years. Much attention is paid to the use of socio-economic indicators along with technical and economic indicators in assessing the mineral resource base. Consequently, due to the development of mineral resources, opportunities arise for creating new jobs, increasing the income of the population, introducing innovative ideas and technologies in practice, and creating a competitive environment in the economy. Therefore, the study of problems in this area in connection with the social sphere and institutions acquires the necessary scientific significance. The article discusses the formation of points of production growth. The main directions of the formation of points of production growth based on mineral-raw material resources are being studied. The distribution of mineral-raw material resources by zones of Karakalpakstan is investigated. In addition, the article talks about the specific features of the formation of reference points of growth. The stages of the formation of growth support points based on the local mineral-raw material resources of Karakalpakstan in 2020-2030 are also considered.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.219

Codex and Gemma teacher scores by category

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

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 head0.006
GPT teacher head0.165
Teacher spread0.159 · 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