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Record W2946665516 · doi:10.2298/sarh190320043j

Environment and health - thirty years of successful implementation of the Montreal protocol

2019· article· en· W2946665516 on OpenAlexaboutno aff
Djordje Jovanović, Mario Lukinović, Zdravko Vitošević

Bibliographic record

VenueSrpski arhiv za celokupno lekarstvo · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicClimate Change and Health Impacts
Canadian institutionsnot available
FundersMinistarstvo Prosvete, Nauke i Tehnološkog Razvoja
KeywordsMedicineMontreal ProtocolContext (archaeology)Protocol (science)Human healthOzone layerEnvironmental healthPathologyAlternative medicineOzone

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.055
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.028
GPT teacher head0.323
Teacher spread0.295 · 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 teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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

Citations9
Published2019
Admission routes1
Has abstractyes

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