Системный кризис при выборе рабочих тел энергетических установок
Bibliographic record
Abstract
The article compiled results of authors’ previous researches and publications on the subject of power installations working bodies’ choice. We present the detailed chronology of a ban on use of working bodies in power engineering as well as the analysis of consequences of a ban. On a large data set, we have shown that the main causes of the systemic crisis of working fluids for power cycles are in the political sphere, and have only the appearance of the officially declared aim of protecting the environment, while the main goal of the company is the whole political nonmilitary capture of markets. Since the goal is achieved with the apparent excess of tasks, crisis of full inability to use anything for the operation of power machines and refrigerating units has occurred. At a time when TNCs impose states super-expensive and dangerous to human health agents, we present experimentally validated data of fluorocarbons and sulfur hexafluoride and propose to move immediately to use these ones as safe and cheap refrigerants. Today version on the causes of ozone anomalies, open by V.L. Syvorotkin (natural hydrogen degassing of the Earth in the rift zones, see in: Man and the Geosphere. Earth Sciences in the 21st Century. I.V. Florinsky, ed. Nova Science Pub Inc. 2010 ), is the most likely. It simply and reliably represented the true cause of death of ozone not only above Antarctica volcanoes, but above the equator and Baikal. This discovery raises the question of fundamental relevance and competence of bans on chlorinated Freon; also inevitably face the question of tremendous scientific fraud of 1986, as well as the question of the coming financial claims against the author of fraud, although Montreal Protocol obligations belong to the category of voluntary.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.026 | 0.009 |
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".