Cosmetic products as an object of technical regulation of the ministry of health. Development of a methodology for the implementation of the technical regulations
Bibliographic record
Abstract
From 2021, cosmetic products are subject to technical regulation of the Ministry of Health, which is responsible for ensuring the implementation of Technical Regulations, approval of guidelines for their application, national standards in accordance with the requirements of Technical Regulations. It was adopted in early 2021. For the first time in Ukraine, the technical regulations for cosmetic products apply to cosmetic products the principles of technical regulation, powers to comply with which are vested in the relevant Ministry of Health.
 The aim of this work is to develop a methodology for implementing the Technical Regulations for cosmetic products as an object of authority of the Ministry of Health.
 As research materials the processes of technical regulation of cosmetic products are studied, logical, investigation methods of research, and also a method of the content analysis are used.
 Results. An analysis of the practice of regulating the circulation of cosmetic products in a number of foreign countries, identified and systematized potential risks in the implementation of the principles of its technical regulation. Based on the analysis of causal relationships in the process of implementing the requirements of the Technical Regulations for cosmetic products, the methodology of its practical application is proposed.
 Conclusions. The tendencies of regulatory policy in relation to cosmetic products in a number of foreign states and Ukraine are established. The analysis of the main provisions of the Technical Regulations for cosmetic products is carried out and the methodology of its introduction is developed
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
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 | 0.005 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.003 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".