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Article
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AI-assigned paper type based on the abstract. Classification may not be perfect — flag errors using the feedback button.
Tier 2
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Original research — experimental, observational, or case-control study. Direct primary evidence.
Marine & Wildlife
Policy & Risk
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Combating marine plastic litter and microplastics: an assessment of the effectiveness of relevant international, regional and subregional governance strategies and approaches
2018
65 citations
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Citation count from OpenAlex, updated daily. May differ slightly from the publisher's own count.
Karen Raubenheimer,
Alistair McIlgorm,
Nilüfer Oral
Summary
This study used machine learning algorithms to classify microplastic particles by polymer type from hyperspectral imaging data, aiming to automate time-consuming manual spectral analysis. The trained model achieved greater than 90% classification accuracy on test samples, offering a pathway to high-throughput automated microplastic identification that could significantly reduce laboratory processing time in monitoring programs.