Risk Management System at an Engineering Enterprise in Conditions of Ensuring Security
Bibliographic record
Abstract
In modern conditions, the problem of the survival of companies, and the preservation and provision of their further development has become particularly relevant. The crisis has engulfed not only individual enterprises but entire industries. The most affected, in particular, is the engineering industry. The main purpose of the study is the formation of a risk management system at an engineering enterprise in terms of ensuring its security. To do this, we applied the IDEF0 modelling methodology with its main elements. The dynamism of the economic environment and the complexity of the links between its elements necessitate the adoption of informed management decisions in the face of risk and uncertainty of future results. Risk management is becoming an obligatory activity for engineering enterprises, implementation of projects, and operations. Based on the results of the study, a basic IDEF0 model of the risk management system at an engineering enterprise in terms of ensuring its security was formed. The study has limitations and, first of all, they relate to the specifics of the activity of engineering enterprises, other areas of activity are not taken into account. Further research requires expanding the model and taking into account not only risks but also threats and direct dangers.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| 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".