Modeling of the Assessment System of the Main Risks of Investing in Engineering Enterprises in the Conditions of the Development of the Knowledge Economy
Bibliographic record
Abstract
The main purpose of the study is to form a theoretical and methodological model for assessing the risks of investing in engineering enterprises in the context of the development of the knowledge economy. To achieve this purpose, it was necessary to apply the modeling methodology through the use of elements of functional processes that are aimed at achieving the goals and objectives. The relevance of the research topic is given by the fact that today engineering enterprises are extremely sensitive to changes in the operating environment and require a high level of investment. According to the results of the study, we have formed a theoretical and methodological decomposition of a two-variant type of modeling of both external (those that do not directly relate to the enterprise but come from outside) and internal risks (those that arise within the enterprise). The study has limitations and, first of all, they relate to the narrow level of the practical application of the model. Its current state implies a theoretical presentation of the possibilities of informing investors about the state of external and internal risks in the activities of engineering enterprises. Further research will include expanding the modeling process and tasks.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".