CHLORINE OXIDE: INDICATOR AND PREDICTOR OF OZONE DEPLETION IN THE WINTER-SPRING STRATOSPHERE OF THE ARCTIC ACCORDING TO AURA MLS OBSERVATIONS
Bibliographic record
Abstract
В феврале 2022 г. разрушение озона развивалось по сценарию, близкому к озоновой аномалии 2020 г. Отношение смеси озона падало на 61% от многолетней (2006-2019 гг.) нормы 14 марта 2022 г. против 96% 27 марта 2020 г. на высоте 20 км в Эврике, Канада. В то же время, отношение смеси ClO росло до 1.1 млрд-1 18 февраля 2022 г. против 1.2 млрд-1 16 марта 2020 г. на высоте 21 км. Позже, 20 марта 2022 г., произошло мажорное потепление, в результате температура в стратосфере поднялась на 20-25 K во всех исследованных пунктах: Эврика, Канада; Ню-Олесунн, Норвегия; Резольют, Канада; Туле, Гренландия. Высокая корреляция колебаний указанных параметров на приблизительно одинаковых высотах их регистрации, а также между общим содержанием O3 and ClO, рассчитанным из профилей указанных параметров, указывает на их тесную взаимосвязь. In February 2022, ozone depletion developed according to a scenario close to the ozone anomaly of 2020. The ozone mixture ratio fell by 61% of the long-term (2006-2019) norm on March 14, 2022, against 96% on March 27, 2020 at an altitude of 20 km in Eureka, Canada. At the same time, the ratio of the ClO mixture increased to 1.1 billion-1 on February 18, 2022 against 1.2 billion-1 on March 16, 2020 at an altitude of 21 km. Later, on March 20, 2022, major warming occurred, as a result, the temperature in the stratosphere rose by 20-25 K in all the studied points: Eureka, Canada; Nu-Alesund, Norway; Resolute, Canada; Thule, Greenland. The high correlation of the fluctuations of these parameters at approximately the same heights of their registration, as well as between the total content of O3 and ClO calculated from the profiles of these parameters, indicates their close relation.
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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 | 0.000 |
| 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".