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BASIC DIRECTIONS OF INNOVATIVE DEVELOPMENT OF THE FOREST PRODUCTS

2020· article· en· W3094834625 on OpenAlexaboutno aff
E. S. Titova, A. Shevchenko

Bibliographic record

VenueActual directions of scientific researches of the XXI century theory and practice · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBioeconomy and Sustainability Development
Canadian institutionsnot available
Fundersnot available
KeywordsRevenueBusinessProduct (mathematics)GeopoliticsChinaResource (disambiguation)Government (linguistics)Forest productNatural resource economicsGlobalizationEconomyInternational tradeEconomicsEconomic policyMarket economyForest managementGeographyPolitical scienceForestryFinancePolitics

Abstract

fetched live from OpenAlex

Currently, in accordance with the processes of globalization and global economic and environmental trends, the Russian government is focusing economic entities on the innovative development of the Russian economy. For the timber industry of the Russian Federation, which ranks first in the world in terms of timber reserves, a transition to innovative development is inevitable. This transition is due to the resource potential of the industry, global environmental trends of the "green economy", the prevailing market relations between the economic entities of the industry, the presence of a bank of scientific and technical and experimental development in the field of timber industry. The analysis of Russia's share in the global forestry market is carried out: the Russian Federation is the world leader in timber reserves, it has 1/5 of the world's forest reserves and, therefore, takes first place; Brazil ranks second in timber reserves, Canada is third and the United States is fourth. The structure of Russia's exports by product groups is examined: the country's most profitable budget item is the export of fuel and energy products, accounting for 64% of the total export structure, and only 3% of the export structure is the export of timber and paper products. Given the development trends of world oil markets and the geopolitical tensions of countries, it can be assumed that in the next 5 years, the total revenue of the Russian Federation from the export of fuel and energy products will significantly decrease and will cease to be the most profitable budget item in the country. Due to the fact that the Russian Federation is a world leader in timber reserves, we believe that the innovative development of the timber industry should be one of the leading areas in the industry development strategy of the Russian Federation, and accordingly in the export strategy of the Russian Federation. The main directions of the innovative development of the timber industry of the Russian Federation in the following sectors are identified: forestry, woodworking industry, pulp and paper industry, chemical production, logging, wooden housing construction.

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How this classification was reachedexpand

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)0.004
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
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 score0.407
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.052
GPT teacher head0.281
Teacher spread0.230 · 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 teacher head, not a consensus.

Study designBench or experimental
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
Published2020
Admission routes1
Has abstractyes

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