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Record W3099835089 · doi:10.22215/etd/2020-14166

Plastic ingestion, retention, and transport in animals from the eastern Canadian Arctic

2020· dissertation· en· W3099835089 on OpenAlexaffabout
Madelaine P.T. Bourdages

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsCarleton University
Fundersnot available
KeywordsPlastic pollutionMicroplasticsArcticMarine debrisDebrisForagingGuanoSeal (emblem)EcologyFisheryBiologyGeographyEnvironmental scienceArchaeology

Abstract

fetched live from OpenAlex

Plastic and microplastic pollution has been recognized as a global concern.I aimed to assess the retention and transport of plastic pollution in the Canadian Arctic using two important animals from the Arctic ecosystem: seals and seabirds.First, I examined 142 seal stomachs from four communities in the eastern Canadian Arctic to identify whether seals are accumulating plastics in their stomachs.No evidence of accumulated plastic debris in seal stomachs was found, suggesting that seals in the eastern Canadian Arctic are likely not exposed to plastics during foraging.Second, the faecal precursors of northern fulmars (Fulmarus glacialis) and thick-billed murres (Uria lomvia) were examined to identify if these birds are excreting microplastics in their guano.Anthropogenic particles were found in both species, however, there was no relationship between the microplastic particles in the faecal precursors and plastic debris found in the stomachs of the same birds.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score0.249

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.010
GPT teacher head0.190
Teacher spread0.180 · 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

Citations0
Published2020
Admission routes2
Has abstractyes

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