Modeling the Application of Anti-Crisis Management Business Introduction for the Engineering Sector of the Economy
Bibliographic record
Abstract
The main purpose of the article is to model the main stages of the implementation of anticrisis management in an engineering enterprise that has a crisis situation. The object of the study is the system of anti-crisis management and business in the engineering sector of the economy. The research methodology involves the use of modern modeling methods that contribute to the achievement of the goals. In particular, the basis is the technique of modeling control processes using functional-graphic elements. As a result, we have chosen a concretely operating engineering enterprise that has crisis signs of development and requires the use of an anti-crisis enterprise. The elements of novelty of the obtained results of the study are presented in the form of established models for overcoming a crisis situation due to the use of anti-crisis management measures. The study is limited by targeting only one engineering enterprise. In the future, it's need to expand the scope of the study in future research work, so that the results can be more generally applicable. Further research needs to expand the application of the methodological approach.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".