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Record W1862638558 · doi:10.1039/c5em00188a

Benthic plastic debris in marine and fresh water environments

2015· article· en· W1862638558 on OpenAlexaff
Patricia L. Corcoran

Bibliographic record

VenueEnvironmental Science Processes & Impacts · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsWestern University
Fundersnot available
KeywordsDebrisMarine debrisBenthic zoneEnvironmental sciencePlastic pollutionSink (geography)Plastic wasteEstuaryLitterOceanographyMicroplasticsGeologyHydrology (agriculture)EcologyGeographyGeotechnical engineeringWaste management

Abstract

fetched live from OpenAlex

This review provides a discussion of the published literature concerning benthic plastic debris in ocean, sea, lake, estuary and river bottoms throughout the world. Although numerous investigations of shoreline, surface and near-surface plastic debris provide important information on plastic types, distribution, accumulation, and degradation, studies of submerged plastic debris have been sporadic in the past and have become more prominent only recently. The distribution of benthic debris is controlled mainly by combinations of urban proximity and its association with fishing-related activities, geomorphology, hydrological conditions, and river input. High density plastics, biofouled products, polymers with mineral fillers or adsorbed minerals, and plastic-metal composites all have the potential to sink. Once deposited on the bottoms of water basins and channels, plastics are shielded from UV light, thus slowing the degradation process significantly. Investigations of the interactions between benthic plastic debris and bottom-dwelling organisms will help shed light on the potential dangers of submerged plastic litter.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0040.003
Science and technology studies0.0010.000
Scholarly communication0.0020.001
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.009
GPT teacher head0.206
Teacher spread0.197 · 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 designObservational
Domainnot available
GenreEmpirical

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

Citations162
Published2015
Admission routes1
Has abstractyes

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