OZONE LAYER DEPLETION: ITS CAUSES AND CONSEQUENCES
Bibliographic record
Abstract
Ozone layer which is a part of the lower stratosphere has been continuously depleting over years. The ozone layer is a part of the atmosphere that contains high concentration of ozone molecules which absorb the harmful ultraviolet rays from the sun and prevents it from reaching the earth surface. Ozone layer depletion is one of the most significant issues in the present-day world. It is getting worse day by day and has become a threat to global environment as well as human civilization. The main sources of ozone layer depletion are the man-made chlorine related substances such as chlorofluorocarbons (CFCs), bromine, halons, carbon tetrachloride, methyl bromide, hydrofluorocarbons etc. When the ozone layer is significantly thinner over a particular region due to the release of ODS (Ozone depleting substances), it is termed as “Ozone Hole”. The main effect of ozone layer depletion is the increase in ultraviolet rays that reaches the earth surface and makes serious ill effects on human beings, genetic changes, growth on plants, marine ecosystem, damage to possessions etc. Growing concern for ozone layer depletion has led to the adaptation of various policies by various countries to bring down the release of ozone depleting substances at an industrial level as well as individual level. This paper tries to assess the causes and consequences of global ozone depletion and presents some protective measures for preventing further depletion of ozone layer.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".