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Record W4396663125 · doi:10.1017/plc.2024.9.pr5

Recommendation: Consistently inconsistent: The false promise of ‘sustainable’ plastics — R1/PR5

2024· peer-review· en· W4396663125 on OpenAlexaff
Justine Ammendolia, Tony R. ‎Walker

Bibliographic record

Venuenot available
Typepeer-review
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsDalhousie University
Fundersnot available
KeywordsComputer scienceArtificial intelligencePsychology

Abstract

fetched live from OpenAlex

This perspective explains why the lack of regulation around bioplastics remains a hurdle for the successful development and implementation of a legally binding agreement (the Global Plastics Treaty) by the United Nations Environment Assembly to curb plastic pollution by 2024. For example, bioplastics have been marketed to consumers as the panacea solution to our plastic waste crisis. Of the >400 million tonnes of plastics produced each year, <1% are bioplastics, but the market value of bioplastics is expected to grow. The rapid growth of the environmentally ‘sustainable’ plastic market has resulted in an overwhelming variety of products with different properties and labels, which has led to widespread public confusion, particularly about disposal guidelines. The umbrella term of ‘bioplastics’ describes plastics that can be fully or partially sourced from biological matter, unlike conventional petroleum-based plastics. Within this family of plastics, products can be ‘biodegradable’, ‘oxo-biodegradable’ and ‘compostable’ depending on their chemical composition and the external conditions required at disposal (end-of-life). However, cases of petroleum-based biodegradable plastics have been referred to as bioplastics, which is inaccurate. Overall, this lack of regulation remains a hurdle for the successful development and implementation of the Global Plastics Treaty.

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)0.001
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.124
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0150.001

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 head0.023
GPT teacher head0.284
Teacher spread0.261 · 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
Published2024
Admission routes1
Has abstractyes

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