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Record W4211115699 · doi:10.1039/d0pp90011g

Environmental effects of stratospheric ozone depletion, UV radiation and interactions with climate change: UNEP Environmental Effects Assessment Panel, update 2019

2020· review· en· W4211115699 on OpenAlexaffabout
G. Bernhard, Rachel Ε. Neale, Paul W. Barnes, Patrick J. Neale, Richard G. Zepp, Stephen R. Wilson, Anthony L. Andrady, Alkiviadis Bais, Richard McKenzie, P. J. Aucamp, Paul J. Young, Ben Liley, Robyn Lucas, Seyhan Yazar, Lesley E. Rhodes, Scott N. Byrne, Loes M. Hollestein, Catherine M. Olsen, Antony R. Young, T. Matthew Robson, Janet F. Bornman, Marcel A. K. Jansen, Sharon A. Robinson, Carlos L. Ballaré, Craig E. Williamson, Kevin C. Rose, Anastazia T. Banaszak, Donat‐Peter Häder, Samuel Hylander, Sten‐Åke Wängberg, Amy T. Austin, Wen-Che Hou, N. D. Paul, S. Madronich, Barbara Sulzberger, Keith R. Solomon, H. Li, Tamara Schikowski, Janice Longstreth, Krishna K. Pandey, Anu Heikkilä, Christopher C. White

Bibliographic record

VenuePhotochemical & Photobiological Sciences · 2020
Typereview
Languageen
FieldEarth and Planetary Sciences
TopicAtmospheric chemistry and aerosols
Canadian institutionsUniversity of Guelph
FundersDivision of Environmental BiologyManchester Biomedical Research CentreBundesministerium für Umwelt, Naturschutz und ReaktorsicherheitMedical Research CouncilLinnéuniversitetetNational Health and Medical Research CouncilAcademy of FinlandScience Foundation IrelandUniversity of WollongongNational Institute for Health and Care ResearchHelsingin YliopistoAustralian Research CouncilU.S. Environmental Protection AgencySmithsonian InstitutionNaturvårdsverketNational Science Foundation
KeywordsMontreal ProtocolOzone layerEnvironmental scienceClimate changeOzone depletionRatificationGreenhouse gasEnvironmental protectionGlobal warmingOzoneEcologyMeteorologyGeographyPolitical scienceBiology

Abstract

fetched live from OpenAlex
No abstract in any covered source. Its absence is recorded, not treated as a negative.

No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.

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 categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.917
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.258
Teacher spread0.239 · 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.

Study designOther design
Domainnot available
GenreReview

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

Citations123
Published2020
Admission routes2
Has abstractno

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