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Record W4394820037 · doi:10.1111/gcb.17279

Environmental plastics in the context of UV radiation, climate change, and the Montreal Protocol

2024· letter· en· W4394820037 on OpenAlexaffabout
Marcel A. K. Jansen, Anthony L. Andrady, Paul W. Barnes, Rosa Busquets, Laura E. Revell, Janet F. Bornman, P. J. Aucamp, Alkiviadis Bais, Anastazia T. Banaszak, G. Bernhard, Laura S. Bruckman, Donat‐Peter Häder, Mark L. Hanson, Anu Heikkilä, Samuel Hylander, Robyn Lucas, Roy Mackenzie, S. Madronich, Patrick J. Neale, Rachel Ε. Neale, Catherine M. Olsen, Rachele Ossola, Krishna K. Pandey, Irina Petropavlovskikh, Sharon A. Robinson, T. Matthew Robson, Kevin C. Rose, Keith R. Solomon, Mads P. Sulbæk Andersen, Barbara Sulzberger, Timothy J. Wallington, Qingwei Wang, Sten‐Åke Wängberg, Christopher C. White, Antony R. Young, Richard G. Zepp, Liping Zhu

Bibliographic record

VenueGlobal Change Biology · 2024
Typeletter
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsUniversity of GuelphUniversity of Manitoba
Fundersnot available
KeywordsMontreal ProtocolClimate changeContext (archaeology)Environmental scienceProtocol (science)Kyoto ProtocolClimatologyEnvironmental resource managementMeteorologyPhysical geographyGeographyOceanographyOzone layerArchaeologyGeologyMedicine

Abstract

fetched live from OpenAlex

There are close links between solar UV radiation, climate change, and plastic pollution. UV-driven weathering is a key process leading to the degradation of plastics in the environment but also the formation of potentially harmful plastic fragments such as micro- and nanoplastic particles. Estimates of the environmental persistence of plastic pollution, and the formation of fragments, will need to take in account plastic dispersal around the globe, as well as projected UV radiation levels and climate change factors.

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)0.004
metaresearch head score (Gemma)0.014
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.224
Threshold uncertainty score0.445

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.014
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0060.003
Scholarly communication0.0030.002
Open science0.0020.002
Research integrity0.0250.017
Insufficient payload (model declined to judge)0.0120.002

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 head0.240
Teacher spread0.220 · 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 designNot applicable
Domainnot available
GenreEditorial

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

Citations9
Published2024
Admission routes2
Has abstractyes

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