OZONE DEPLETING SUBSTANCES ELIMINATION MANAGEMENT: THE SUCCESS STORY OF MACEDONIA
Bibliographic record
Abstract
Man, with its activities, produces and uses substances that have negative impact on the environment and the human health, and can cause an economic damage. Consequently, they have a great impact on quality of life. Among the most harmful chemicals are Ozone Depleting Substances that are subject of regulation with international conventions. This Paper supports the fact that each country has to undertake national efforts for ozone depleting substances reduction and elimination. In that respect, the general objective of the Paper is to present the Macedonian unique experience regarding its efforts to reduce or eliminate these substances. The following two aspects were subject to the research: national legislation which regulates the Ozone Depleting Substances import and export as well as the implementation of the projects that resulted with the elimination of Ozone Depleting Substances quantities in the period 1995 – 2010. The research outcomes confirm the starting research hypothesis i.e. that with adequately created and implemented national action, the amount of Ozone Depleting Substances consumption can dramatically fall. Key words: Montreal Protocol, Vienna Convention, Ozone Unit, Macedonia, Phase-out.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".