Formation of a Model of Legal Protection of Competitive Advantages in the System of Innovation Management of Sustainable Development and Planning
Bibliographic record
Abstract
The main purpose of the article is the formation a model for the legal protection of competitive advantages in the system of innovative management of sustainable development and planning. Based on the results of the research, a model of the legal protection of competitive advantages in the system of innovative management of sustainable development and planning and its key elements was presented. The methodology involves the use of an effective and popular modeling technique, which is able to cope with the tasks. The main elements of the proposed methodological approach for the modeling process were presented. The main stages of achieving the goals of modeling are determined. The main multifunctional model for providing legal protection of competitive advantages in the system of innovation management is presented. It is the presented model that represents a new methodological approach, characterized by flexibility and functionality. The study has limitations in the form of the inability to effectively evaluate the model in practice in many socio-economic systems due to the lack of access. Further research should be devoted to the possibilities of expanding the model and its elements.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".