Analysis of total ozone trends in the Iberian Peninsula using satellite data
Bibliographic record
Abstract
This work is focused on the study of the total ozone column (TOC) trends over the Iberian Peninsula during the last 30 years (1979-2009). This analysis is carried out using satellite TOC data and it is divided into two sub-periods in order to detect changes in the ozone trend pattern: from 1979 to 1994 using the NASA Total Ozone Mapping Spectrometer (TOMS) and from 1995 to 2009 by means of the ESA Global Ozone Monitoring Experiment (GOME). The analysis of the long-term ozone trends is performed using annual mean time series derived from the average of the deseasonalized monthly TOC series. The results show that the ozone depletion was statically significant at the 95% confidence level during the first sub-period (1979-1994) in the entire region of study, with linear trends from -4.5 %/decade to -2.9 %/decade. These linear trends presented a clear dependence on latitude, being higher for the Northerner locations than for the Southerner. By contrast, the analysis of the second sub-period of study (1995-2009) presented positive ozone trends from +0.6 %/decade to +1.8 %/decade (only statically significant in four of nine locations of study), indicating that the ozone layer may be responding as expected to the controls on ozone-depleting substances imposed by the Montreal Protocol. Additionally, a seasonal trend analysis is performed using the average of the deseasonalized monthly values for each season of the year. The seasonal analysis showed that while the negative ozone trends during the first sub-period of study were statically significant in the springtime and summertime, the positive seasonal trends during the second sub-period did not show any statistically significance.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| 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".