No microplastics detected in the first assessment of Atlantic walrus stomachs from Nunavut, Canada
Bibliographic record
Abstract
As plastic pollution continues to persist at a global level, the Arctic has drawn increased research interest as a possible sink for marine pollutants. Plastic and microplastics are highly durable and can be transported across vast distances. To date, only a handful of studies have directly assessed microplastics in Arctic mammals. In Canada, it is still unclear whether they show a concrete propensity for microplastic retention and ingestion. Atlantic walruses ( Odobenus rosmarus rosmarus (Linnaeus, 1758)) are economically and culturally important for Inuit and are key predators in Arctic marine ecosystems. Here, we present the first assessment of microplastic pollution in Canadian walruses and the first gastrointestinal assessment of microplastic in walruses globally. Since microplastics accumulate in benthic sediment and animals, we expected that walruses may ingest and retain microplastic contaminants when sifting in search of prey or when eating contaminated bivalves and invertebrates. We detected no microplastics ≥80 µm in our evaluation of 36 walruses from five communities in NU, Canada. Our results suggest that walruses in this region do not retain microplastic particles ≥80 µm in their stomachs, which is consistent with findings in other pinnipeds that have been evaluated in Arctic Canada.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".