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Record W4367149308 · doi:10.1021/cen-09931-polcon3

Ozone treaty holds down atmospheric CO₂ levels

2021· article· en· W4367149308 on OpenAlexaboutno aff
CHERYL HOGUE

Bibliographic record

VenueC&EN Global Enterprise · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMontreal ProtocolOzone layerStratosphereOzoneCarbon sinkEnvironmental scienceAtmospheric sciencesKyoto ProtocolMeteorologyGreenhouse gasEcosystemGeographyEcologyBiology

Abstract

fetched live from OpenAlex

An international treaty to protect stratospheric ozone is slowing the growth of atmospheric levels of carbon dioxide, according to a team of scientists ( Nature 2021, DOI: 10.1038/s41586-021-03737-3 ). The 1987 Montreal Protocol on Substances that Deplete the Ozone Layer is reversing loss in the stratosphere of the triatomic molecule that screens the Earth’s surface from the sun’s ultraviolet rays, protecting both humans and ecosystems from damage. One consequence is that land plants are healthier and able to absorb more CO 2 for photosynthesis than they would have absent the pact, the researchers say. Led by Paul J. Young , an atmospheric scientist at Lancaster University in the UK, the team used computer models to estimate the benefits of avoided increases in UV radiation on terrestrial plants and their ability to act as a carbon sink. The researchers estimate that by 2080–99 the Montreal Protocol will lead to atmospheric CO

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.819
Threshold uncertainty score0.854

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.019
GPT teacher head0.324
Teacher spread0.304 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
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
Published2021
Admission routes1
Has abstractyes

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