Environment and health - thirty years of successful implementation of the Montreal protocol
Bibliographic record
Abstract
The Protocol on Ozone Depleting Substances (ODS) was signed in 1987 in Montreal. The main goal of the protocol is the international consensus and action regarding the drastic decrease of production and use of these substances, which results in increased UV radiation and consequently has a negative impact on human health and ecosystem. Besides the review of the ?legal and technical? implementation of the protocol until now and the withdrawal of ODS from use, this paper specially stresses the analysis of available research results regarding the positive impact on health, in correlation with the implementation of the Montreal Protocol (MP). Due to the results of the thirty-year-long use until now, the MP is referred to as one of the most successful international agreements, not only in the field of environmental protection, but also in the field of human health protection in relation to it, within a certain context. Besides the reduced negative impact of ultraviolet radiation (UV) to the ecosystem and people, we are also facing a reduced occurring trend of skin cancer, cataracts, and immune system diseases worldwide. Without the MP and its implementation, millions of people would have died because of UV radiation and the previously mentioned diseases. The treatment costs and the pressure to the health system in all the countries worldwide would have enormously increased because of that.
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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 | 0.069 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.005 |
| Scholarly communication | 0.008 | 0.003 |
| Open science | 0.004 | 0.007 |
| Research integrity | 0.006 | 0.006 |
| Insufficient payload (model declined to judge) | 0.008 | 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".