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Cosmetic products as an object of technical regulation of the ministry of health. Development of a methodology for the implementation of the technical regulations

2021· article· en· W3211911293 on OpenAlexaff
Iryna Kazakova, Svitlana Kovalenko, V. O. Lebedynets, Daria Bondarenko, Viktoriya Kazakova

Bibliographic record

VenueScienceRise Pharmaceutical Science · 2021
Typearticle
Languageen
FieldMedicine
TopicSkin Protection and Aging
Canadian institutionsAdvanced Micro Devices (Canada)
Fundersnot available
KeywordsChristian ministryObject (grammar)BusinessEngineering ethicsEngineering managementRisk analysis (engineering)EngineeringProcess managementComputer sciencePolitical scienceLawArtificial intelligence

Abstract

fetched live from OpenAlex

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.035
metaresearch head score (Gemma)0.032
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.035
Threshold uncertainty score0.188

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0350.032
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0050.003
Science and technology studies0.0030.007
Scholarly communication0.0070.005
Open science0.0020.004
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0080.003

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.

Opus teacher head0.198
GPT teacher head0.512
Teacher spread0.314 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreMethods

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".

Quick stats

Citations2
Published2021
Admission routes1
Has abstractyes

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