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Record W4308447285 · doi:10.18280/ijdne.170512

Russian Timber Industry: Current Situation and Modelling of Prospects for Wood Biomass Use

2022· article· en· W4308447285 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.

venuePublished in a venue whose home country is Canada.
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

VenueInternational Journal of Design & Nature and Ecodynamics · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBioeconomy and Sustainability Development
Canadian institutionsnot available
Fundersnot available
KeywordsLoggingVariety (cybernetics)Biomass (ecology)AgricultureState (computer science)Wood industryCurrent (fluid)BusinessNatural resource economicsAgricultural economicsGeographyEngineeringForestryEconomicsEcologyArchaeologyMathematics

Abstract

fetched live from OpenAlex

The purpose of this article is to investigate certain aspects of the current state of the Russian timber industry. The Boston Consulting Group matrix is created to illustrate the current state of the industry in a variety of sectors. The industry's growth rates in various federal districts of the country are examined. Models of changes in volume indicators of the Krasnoyarsk Territory's timber industry output, prices, and individual qualitative characteristics for round timber are obtained. This region is fascinating due to the variety of agricultural products and climatic conditions (logging despite the High North conditions). The study recognizes the significance of expanding the use of the entire tree biomass and stimulating integration associations in the forest industry.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.662
Threshold uncertainty score0.140

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 head0.029
GPT teacher head0.249
Teacher spread0.220 · 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