Improving Efficiency of Asset Management in the Context of Ensuring Competitiveness of Mechanical Engineering Enterprises in Developing Countries
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The research paper deals with the formation of new scientific solutions regarding increasing the efficiency of asset management in the context of ensuring the competitiveness of mechanical engineering enterprises in developing countries. The study noted the disparity in the development of economically developed and developing countries. It is revealed that one of the main aspects of such disparity is the competitiveness of both the economies of the countries as a whole, and of individual industries and enterprises. At the same time, the importance of ensuring the competitiveness of mechanical engineering enterprises in developing countries was noted, taking into account their potential and opportunities for stimulating GDP and employment growth in these countries. The relationship between the competitiveness of mechanical engineering enterprises and their asset management is established. The main problems of asset management at the mechanical engineering enterprises in the developing countries are localized, and the ways of their elimination are proposed taking into account the division of enterprises into those operating as part of the transnational and foreign corporations, large enterprises with national capital, medium and small enterprises with national capital. A considerable range of problems regarding the asset management in small and medium enterprises was noted. Directions of further scientific researchers are suggested.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it