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Record W2107340913 · doi:10.1071/en10072

Trends of polyfluoroalkyl compounds in marine biota and in humans

2010· article· en· W2107340913 on OpenAlexaff
Renate Sturm, Lutz Ahrens

Bibliographic record

VenueEnvironmental Chemistry · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicPer- and polyfluoroalkyl substances research
Canadian institutionsToronto East General HospitalEnvironment and Climate Change Canada
Fundersnot available
KeywordsPerfluorooctaneBiotaEnvironmental chemistryContext (archaeology)Trophic levelFood chainEnvironmental scienceFish <Actinopterygii>ChemistryEcologyGeographyBiologyFisherySulfonate

Abstract

fetched live from OpenAlex

Environmental context Polyfluoroalkyl compounds are used in a variety of industrial and consumer applications, including polymer production and for surface treatment of textiles and paper. Research over the last 10 years has shown that these compounds are ubiquitous environmental contaminants – they are extremely persistent, show toxic effects and accumulate in the food chain. We evaluate global, temporal and spatial trends of these important emerging contaminants. Abstract This review gives an overview of existing knowledge of polyfluoroalkyl compounds (PFCs) in humans and in marine biota. Temporal trends and spatial distribution of PFCs were globally compared in humans, marine mammals, seabirds and fish. In general, PFC concentrations in the environment have increased significantly from the beginning of the production up to the 1990s. After the phase-out of perfluorooctane sulfonyl fluoride (POSF) production starting in 2000, PFC concentrations in humans generally decreased. In marine biota no clear temporal trends were observed. The temporal trends depended on the species, their trophic levels and the geographical locations. PFC patterns in humans and in marine wildlife species were compared regarding perfluorooctane sulfonate (PFOS), perfluorooctanoate (PFOA), their shorter and longer chain homologues (C4–C15) and precursor compounds. Finally knowledge gaps were identified and recommendations for future work were presented.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.275
Threshold uncertainty score0.988

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0130.000

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 head0.006
GPT teacher head0.229
Teacher spread0.223 · 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.

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

Citations67
Published2010
Admission routes1
Has abstractyes

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