Prediction of ozone layer thickness in troposphere based on continuously measurement of ultra-violet radiation in Gulf cooperation council (GCC)
Bibliographic record
Abstract
Troposphere Ozone layer acts as a shield against all ultraviolet radiation approaching the planet Earth through absorption. It was noticed in mid 80s that ozone layer has thinned on the poles of the planet due to release of man-made substances commonly known as Ozone Depleting Substances, (ODS) into its atmosphere. The consequences of this change are adverse as the harmful radiations reach to the surface of the earth, strongly influencing the crops yield and vegetation. These radiations are major cause of skin cancer that has long exposure to UV radiation. United States Environmental Protection Agency and European Community have imposed strict regulations to curb the emission of ODS and phase out schedules for the manufacture and use of ODS that was specified by Montreal Protocol in 1987. This research program deals with data analysis of ozone layer thickness and measured ultra-violet radiation that have been obtained at an altitude of 8 km from Abu Dhabi Monitoring station. The ozone layer thickness in stratosphere has been correlated with measured ultraviolet radiation above the Gulf Cooperation Council (GCC). The influence of import of ozone depletion substances for the last decade and other factors that strongly affect the ozone layer thickness in stratosphere were discussed in the final report submitted to Public. The dependency of ozone layer thickness on ambient pollutant levels is discussed in detail.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".