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Record W2113855495 · doi:10.1002/grl.50358

Climate impact of stratospheric ozone recovery

2013· article· en· W2113855495 on OpenAlexaboutno aff
Slimane Bekki, Alexandru Rap, Virginie Poulain, Sandip Dhomse, Marion Marchand, Franck Lefèvre, Piers Forster, Sophie Szopa, Martyn P. Chipperfield

Bibliographic record

VenueGeophysical Research Letters · 2013
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric Ozone and Climate
Canadian institutionsnot available
FundersScheme for Promotion of Academic and Research CollaborationNatural Environment Research CouncilEuropean CommissionSight Research UKRoyal Society
KeywordsOzone layerStratosphereOzoneAtmospheric sciencesOzone depletionEnvironmental scienceRadiative forcingGreenhouse gasMontreal ProtocolClimatologyForcing (mathematics)Climate changeMeteorologyPhysicsGeology

Abstract

fetched live from OpenAlex

Abstract Past stratospheric ozone depletion has acted to cool the Earth's surface. As the result of the phase‐out of anthropogenic halogenated compounds emissions, stratospheric ozone is projected to recover and its radiative forcing (RF‐O3 ~ −0.05 W/m2 presently) might therefore be expected to decay in line with ozone recovery itself. Using results from chemistry‐climate models, we find that, although model projections using a standard greenhouse gas scenario broadly agree on the future evolution of global ozone, they strongly disagree on RF‐O3 because of a large model spread in ozone changes in a narrow (several km thick) layer, in the northern lowermost stratosphere. Clearly, future changes in global stratospheric ozone cannot be considered an indicator of its overall RF. The multi‐model mean RF‐O3 estimate for 2100 is +0.06 W/m2 but with a range such that it could remain negative throughout this century or change sign and reach up to ~0.25 W/m2.

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)0.000
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 score0.017
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.025
GPT teacher head0.292
Teacher spread0.266 · 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

Citations49
Published2013
Admission routes1
Has abstractyes

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