Bibliographic record
Abstract
There are a variety of contexts in which human actions have the potential to have major impacts on the surrounding environment. One of them is the depletion of the ozone layer. The purpose of this study is to investigate and review. The purpose of this study is to investigate the background, causes, processes, and biological implications of ozone layer depletion, as well as the preventative steps that have been taken to safeguard this layer of the atmosphere. Both chlorofluorocarbons and halons are very effective ozone-depleting substances. The expected increase in the levels of UV radiation received at the surface of the planet and the impact that this will have on both human health and the environment is one of the primary reasons for the widespread worry over the depletion of the ozone layer. The outlook for the ozone layer's recovery is still unknown. As a result of regulation, halogen loading is expected to decrease, which should lead to an increase in the quantity of stratospheric ozone in the future, assuming that no other changes take place. However, the future behaviour of ozone will also be influenced by other factors, such as the changing abundances of methane, nitrous oxide, water vapour, and sulphate aerosol in the atmosphere, as well as the changing temperature.
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 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) | 0.019 | 0.008 |
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".