Bibliographic record
Abstract
In the winter of 2010–2011, ozone levels above the Arctic declined to record lows, creating the first Arctic ozone hole, similar to the well‐known Antarctic ozone hole. Scientists believe the ozone depletion was due partly to unusually cold temperatures in the stratosphere above the Arctic, as colder stratospheric temperatures make ozone‐destroying chemicals such as chlorine more active. As global climate change continues, the Arctic stratosphere is expected to get colder, but levels of ozone‐destroying chemicals should decline, as emissions of these chemicals were banned by the Montreal Protocol. To try to learn more about Arctic ozone dynamics and determine whether the Arctic ozone hole is likely to recur, Sinnhuber et al. looked at satellite observations of temperature, ozone, water vapor, and chemicals that affect ozone in the Arctic atmosphere. They also used a model to determine how sensitive ozone levels are to stratospheric temperatures and chemistry. They found that their model accurately reproduced measured conditions. Their model suggests that stratospheric temperatures 1°C lower than in the 2010–2011 winter would result in locally nearly complete ozone depletion in the Arctic lower stratosphere with current levels of chemicals. A 10% reduction in ozone‐depleting chemicals would be offset by a 1°C decrease in stratospheric temperatures.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.003 | 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".