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Record W4388859889 · doi:10.1038/s41467-023-42637-0

Potential drivers of the recent large Antarctic ozone holes

2023· article· en· W4388859889 on OpenAlexaboutno aff
Hannah E. Kessenich, Annika Seppälä, Craig J. Rodger

Bibliographic record

VenueNature Communications · 2023
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
FundersMinistry of Business, Innovation and Employment
KeywordsOzone depletionOzonePolar vortexOzone layerStratosphereEnvironmental scienceAtmospheric sciencesSouthern HemisphereClimatologyMontreal ProtocolNorthern HemisphereSpring (device)LatitudeClimate changeOceanographyMeteorologyGeographyGeologyPhysics

Abstract

fetched live from OpenAlex

The past three years (2020-2022) have witnessed the re-emergence of large, long-lived ozone holes over Antarctica. Understanding ozone variability remains of high importance due to the major role Antarctic stratospheric ozone plays in climate variability across the Southern Hemisphere. Climate change has already incited new sources of ozone depletion, and the atmospheric abundance of several chlorofluorocarbons has recently been on the rise. In this work, we take a comprehensive look at the monthly and daily ozone changes at different altitudes and latitudes within the Antarctic ozone hole. Following indications of early-spring recovery, the October middle stratosphere is dominated by continued, significant ozone reduction since 2004, amounting to 26% loss in the core of the ozone hole. We link the declines in mid-spring Antarctic ozone to dynamical changes in mesospheric descent within the polar vortex, highlighting the importance of continued monitoring of the state of the ozone layer.

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 imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0000.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.015
GPT teacher head0.255
Teacher spread0.240 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations31
Published2023
Admission routes1
Has abstractyes

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