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Record W4407156950 · doi:10.33271/crpnmu/78.064

Peat deposits in Ukraine and in the world: current state, reserves, problems of geological and economic evaluation

2024· article· en· W4407156950 on OpenAlexaboutno aff
K Коlchev

Bibliographic record

VenueCollection of Research Papers of the National Mining University · 2024
Typearticle
Languageen
FieldEngineering
TopicEngineering and Environmental Studies
Canadian institutionsnot available
Fundersnot available
KeywordsCurrent (fluid)PeatState (computer science)GeologyEarth scienceGeochemistryMining engineeringNatural resource economicsEnvironmental protectionGeographyArchaeologyEconomicsComputer scienceOceanography

Abstract

fetched live from OpenAlex

Purpose. Determination of the current state of peat reserves in Ukraine and in the world. The methods. The work uses general scientific methods of research – empirical and theoretical (analysis, generalization, comparison, explanation, classification), as well as methods of statistical processing and display of analyzed information. Findings. The data on the current state of peat reserves in the leading peat-producing countries of the world, Europe, and Ukraine are analyzed. 57% of the world's peat reserves are located in regions with boreal climates, but at the same time, tropical regions account for 21% of the reserves. This makes countries with large territories in the north (in particular, Canada and the United States) and in the tropics, in particular, Indonesia, the leaders. It was determined that there is no concept for the development of the peat industry in Ukraine. The problems of geological and economic assessment of peat deposits in Ukraine are the outdated data on the type of use, as well as environmental issues. The originality.For the first time, the article identifies the urgent problem of reassessing geological and industrial peat reserves for existing enterprises and potential peat deposits in Ukraine. The analysis of the data shows that part of the reserves since the first geological exploration 40–60 years ago could have been converted to energy peat, which significantly increases the forecast value of reserves and requires taking this factor into account among other geological risks in the geological and economic assessment of these deposits. The environmental component of the problem of assessing geological risks for peat deposits in Ukraine has been further developed. Practical implementation. The analysis of the current state of peat reserves allows us to clarify and inform the scientific community about the current state of peat reserves in Ukraine and the world, as the use of peat as a raw material in various industries is becoming relevant to address the problems of overcoming the consequences of the post-war economic crises and the development of innovative technologies.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.003
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0000.001
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 head0.047
GPT teacher head0.296
Teacher spread0.249 · 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 designObservational
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
Published2024
Admission routes1
Has abstractyes

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