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Record W4412924502 · doi:10.1017/plc.2025.10020.pr7

Recommendation: Complexity in managing plastics — R1/PR7

2025· peer-review· en· W4412924502 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldEnvironmental Science
TopicChemistry and Chemical Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsComputer science

Abstract

fetched live from OpenAlex

This letter discusses the complex nature of plastics, why regulating plastics is a ‘wicked problem’, and the implications of a life cycle approach. The draft Global Plastics Treaty attempts to address two key problems: the cap on production and the problem of chemical additives in plastics. As a ‘wicked’ problem with many conflicting interests, dealing with plastics requires a holistic life cycle approach completely different from the Montreal Protocol. Strict and enforced limits on polymer production would reduce plastics pollution and also encourage a reduction in the range of additives, as limiting production would make mechanical or chemical recycling more viable. Used plastics need to be turned into a commodity rather than a waste, and reducing and standardising the number of different chemical formulations would help by reducing the number of chemicals to be regulated. To achieve these objectives, this letter argues for a regulatory approach based on a forensic analysis that applies extended environmental systems analysis to all the life cycle stages of the plastics value chain.

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 categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.049
Threshold uncertainty score0.952

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)0.0490.000

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 head0.037
GPT teacher head0.284
Teacher spread0.247 · 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 designNot applicable
Domainnot available
GenreOther

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
Published2025
Admission routes1
Has abstractyes

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