The Need for Comprehensive Regulation of Mineral Water Utilization in Ukraine
Bibliographic record
Abstract
The topicality of this research emanates from the lack of comprehensive legal regulation in the field of water use and protection of water resources, including the territories where they are located. A significant part of the discussion centers around the lack of adequate legal protection for natural complexes, objects, and bodies of mineral and freshwaters, both within protected areas and beyond them. The presence of a territory with significant diversity in water types, including variations in object, chemical composition, temperature regime, and physical properties, creates unique opportunities for the development of recreation and the resort industry. This potential is now becoming the focus of a new discussion. At balneological resorts, natural mineral waters are used as the main therapeutic factor. They are recommended both for external use (baths, showers, pools) and for internal use (inhalations, drinking, rinsing and irrigation). The issue of maintaining compliance of the water quality with sanitary standards regarding consumption and other use of water for medical or recreational purposes is particularly acute. Each exploited deposit of a balneological resort, sanatorium and water bottling plant is subject to the sanitary protection. However, there is a significant risk that not all waterworks systems are officially protected. Thus, environmental control, monitoring and compliance with sanitary regimes, as well as fees for special water use, etc., go beyond the legal regulation. Ignoring environmental problems such as pollution, littering, and irrational use of natural resources is a major issue in modern Ukraine, further exacerbated by the military actions of the Russian Federation, which cause irreparable damage to the environment. Instability introduces new challenges, which is why the main purpose of this paper is to analytically address the need for comprehensive regulation of mineral water utilization in Ukraine. This study highlights that the social value of mineral waters is crucial for human health and the economic development of the State. However, the outstanding goal is to bring to the public the need to preserve unique natural factors that affect the quality of fresh and mineral waters.
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 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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".