A concept of transition to the best available technology as a basis for sustainable development of power industry
Bibliographic record
Abstract
The high level of the negative impact on the environment in the Russian Federation remains steady for many years. Significant and specific contribution to the current level of pollution is made by the companies of the energy sector, which is among the top three in terms of the negative impact on the environment. The planned transition to technological regulation system is based on the use of the best available technology (BAT). The concept formation of the transition to BAT is a challenge for the industry. The basis of the concept is the unified approach development, harmonized with the European approaches, Russian practice and methodological guidelines for BAT identification, which will facilitate informational and technical implementation of BAT in the economy entities of the energy sector. To solve this problem, the authors developed a model for BAT implementation, using a step-by-step logical approach to decision-making. This approach is based on a comparison of the environmental protection measures effectiveness with costs that the economic entity should bear to avoid or minimize man-made impact in normal conditions of management, that is, before BAT introduction. The economic expediency evaluation of the technology in a particular industry is an integral part of BAT implementation concept.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".