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Record W2803113060 · doi:10.1371/journal.pone.0196005

Abundance and distribution of microplastics within surface sediments of a key shellfish growing region of Canada

2018· article· en· W2803113060 on OpenAlexafffundabout
Tamara N. Kazmiruk, V. D. Kazmiruk, Leah Bendell

Bibliographic record

VenuePLoS ONE · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsSimon Fraser University
FundersSimon Fraser University
KeywordsMicroplasticsSedimentBenthic zoneEnvironmental scienceOysterAbundance (ecology)ShellfishPacific oysterEnvironmental chemistryCrassostreaBivalviaEcologyBiologyFisheryChemistryAquatic animalMolluscaFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The abundance and distribution of microplastics within 5 sediment size classes (>5000 μm, 1000-5000 μm, 250-1000 μm, 250-0.63 μm and < 0.63 μm) were determined for 16 sites within Lambert Channel and Baynes Sound, British Columbia, Canada. This region is Canada's premier growing area for the Pacific oyster (Crassostrea gigas). Microplastics were found at all sampling locations indicating widespread contamination of this region with these particles. Three types of microplastics were recovered: microbeads, which occurred in the greatest number (up to 25000/kg dry sediment) and microfibers and microfragments, which were much less in number compared with microbeads and occurred in similar amounts (100-300/kg dry sediment). Microbeads were recovered primarily in the < 0.63 μm and 250-0.63 μm sediment size class, whereas microfragments and microfibers were generally identified in all 5 sediment size classes. Abundance and distribution of the three types of microplastics were spatially dependent with principal component analysis (PCA) indicating that 84 percent of the variation in abundance and distribution was due to the presence of high numbers of microbeads at three locations within the study region. At these sites, microbeads expressed as a percent component of the sediment by weight was similar to key geochemical components that govern trace metal behavior and availability to benthic organisms. Microbeads have been shown to accumulate metals from the aquatic environment, hence in addition to the traditional geochemical components such as silt and organic matter, microplastics also need to be considered as a sediment component that can influence trace metal geochemistry. Our findings have shown that BC's premier oyster growing region is highly contaminated with microplastics, notably microbeads. It would be prudent to assess the degree to which oysters from this region are ingesting microplastics. If so, it would have direct implications for Canada's oyster farming industry with respect to the health of the oyster and the quality of product that is being farmed and sets an example for other shellfish growing regions of the world.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.996

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)0.0000.000

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 head0.013
GPT teacher head0.170
Teacher spread0.157 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations75
Published2018
Admission routes3
Has abstractyes

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