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Record W3099629822 · doi:10.3390/jmse8110945

A Review of the Production, Recycling and Management of Marine Plastic Pollution

2020· review· en· W3099629822 on OpenAlexaff
Ibrahim Issifu, U. Rashid Sumaila

Bibliographic record

VenueJournal of Marine Science and Engineering · 2020
Typereview
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsUniversity of British ColumbiaFisheries and Oceans Canada
Fundersnot available
KeywordsPlastic pollutionPollutionMarine pollutionScope (computer science)Marine ecosystemMarine lifeEnvironmental planningEnvironmental scienceSustainable developmentEnvironmental protectionEnvironmental resource managementMarine debrisProduction (economics)BusinessNatural resource economicsEcosystemEcologyOceanographyComputer scienceEconomicsBiology

Abstract

fetched live from OpenAlex

The human attachment to plastic has intensified recently due to its lightweight, versatility, low-cost and durability and so has the damage to the marine environment as marine plastic pollution has correspondingly increased. As a result, there has been increasing concern on the issue of marine plastic pollution. Policy-based organizations such as the United Nations Environment Programme have drawn public attention to the scope, magnitude and impacts of marine pollution in recent decades. Research on marine pollution can play a significant role in contributing to policy-making processes in support of the United Nations Sustainable Development Goal on Life Below Water (SDG 14), by providing scientific analysis on the effects and sources of marine plastic pollution. This paper provides a theoretical and empirical overview of marine plastic pollution and its potential effects on marine ecosystems. It also discusses SDGs that are relevant to marine plastic pollution and suggest priorities for further research.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.006
Threshold uncertainty score0.019

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0040.005
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.002

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 head0.012
GPT teacher head0.226
Teacher spread0.213 · 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
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

Citations51
Published2020
Admission routes1
Has abstractyes

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