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Record W2118784462 · doi:10.1029/2012eo080011

Record Arctic ozone depletion could occur again

2012· article· en· W2118784462 on OpenAlexaboutno aff
Ernie Balcerak

Bibliographic record

VenueEos · 2012
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
Fundersnot available
KeywordsOzone depletionStratosphereOzoneArcticMontreal ProtocolOzone layerEnvironmental scienceAtmospheric sciencesClimatologyArctic geoengineeringMeteorologyOceanographyArctic ice packGeographyGeology

Abstract

fetched live from OpenAlex

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.095
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0080.003

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 head0.020
GPT teacher head0.229
Teacher spread0.209 · 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; both teacher heads agree on what is shown here.

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

Citations0
Published2012
Admission routes1
Has abstractyes

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