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Record W4408290412 · doi:10.1016/j.crsus.2025.100341

Ubiquitous global use of persistent PFAS threatens Arctic Indigenous peoples for decades to come

2025· article· en· W4408290412 on OpenAlexaff
Christian Sonne, Kim Gustavson, Rossana Bossi, Jens Søndergaard, Jean‐Pierre Desforges, Eva Cecilie Bonefeld‐Jørgensen, Runé Dietz

Bibliographic record

VenueCell Reports Sustainability · 2025
Typearticle
Languageen
FieldEnvironmental Science
TopicPer- and polyfluoroalkyl substances research
Canadian institutionsUniversity of Winnipeg
FundersHORIZON EUROPE Framework ProgrammeMiljøstyrelsen
KeywordsIndigenousArcticThe arcticGeographyEnvironmental planningOceanographyEcologyBiologyGeology

Abstract

fetched live from OpenAlex

Per- and polyfluoroalkyl substances (PFAS) are found in the environment worldwide due to their ubiquitous usage, global transport, and biological persistence. Here, we estimate the temporal dietary exposure to long-range-transported PFAS during 2006–2020 in the East Greenland Ittoqqortoormiit (Scoresby Sound) community based on consumption of traditional marine foods as compared with internationally established tolerable weekly intake (TWI) for immune toxicity of 4.4 ng/kg body weight. We found a biomagnification factor of 4–10 between ringed seal:polar bear and estimate that ∼90% of the Ittoqqortoormiit community exceeded the established ∑ 4 PFAS TWI by 13-fold through consumption of polar bears and ringed seals. We estimate that the average inhabitant will continue to exceed established toxicity guidelines until 2090, posing the risk of immune suppression and disease susceptibility. Our findings emphasize the need for additional regulation of PFAS and the development of non-toxic sustainable compounds through international collaboration, not least through the Stockholm Convention.

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)0.001
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 score0.151
Threshold uncertainty score0.301

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.017
GPT teacher head0.299
Teacher spread0.281 · 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

Citations5
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueCell Reports SustainabilitySame topicPer- and polyfluoroalkyl substances researchFrench-language works237,207