The Solution of Applied Problems of Optimization of Stability of System "Environment-Man-Technics"
Bibliographic record
Abstract
Justified the application of the basic principles of the theory of dynamical systems in the study of the elemental balance of system “environment-man-technique” (EMT). It is established that the irreducibility of the system properties to the sum of the properties of its constituents leads to contradictions. The aim of the research is the development of methods to detect contradictions in the system EMT by assessing the consistency of its elements. The methodological base of the adopted theoretical generalization of scientific provisions of the leading scientists of the industry, constituting the content of the theory of machines. When solving the tasks, we used methods of systems theory, the theory of mathematical statistics, the theory of risk and catastrophe theory, methods of similarity and dimensions. Empirical dependences were based on regression analysis and are presented in the dimensionless form. In the process of research assessed the consistency of the elements for an idealized systems, which offered the reference indicators of their energy sustainability. Considered the behavior of each element of the system for the whole period of the life cycle in real conditions, obtained graphic dependences. The revealed contradictions in the interaction elements of the system EMT showed that current tasks, manmade and implemented technical means lead to the loss of stable equilibrium inside the “environment”, which in turn affects the balance of life-support of the person item, evidence in the form established that in both cases, a loss of equilibrium state calls a “technique”. Developed histogram situational assessment model perturbation in the system EMT can not only set the emerging element of contradiction, but also to develop a model of governance that ensures the balance of the elements of the system with a high level of security.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
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".