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Record W2318654047 · doi:10.1021/es301160r

Enantiospecific Perfluorooctane Sulfonate (PFOS) Analysis Reveals Evidence for the Source Contribution of PFOS-Precursors to the Lake Ontario Foodweb

2012· article· en· W2318654047 on OpenAlexafffundabout
Brian J. Asher, Yuan Wang, Amila O. De Silva, Sean Backus, Derek C. G. Muir, Charles S. Wong, Jonathan W. Martin

Bibliographic record

VenueEnvironmental Science & Technology · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicPer- and polyfluoroalkyl substances research
Canadian institutionsUniversity of WinnipegEnvironment and Climate Change CanadaUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsPerfluorooctaneEnvironmental chemistryBioaccumulationChemistryPerfluorooctanoic acidInvertebrateSculpinSedimentEcologySulfonateFish <Actinopterygii>BiologyFishery

Abstract

fetched live from OpenAlex

Exposure to perfluorooctane sulfonate (PFOS) may arise directly, from emission and exposure to PFOS itself, or indirectly via the environmental release and degradation of PFOS-precursors. Human serum enantiomer fractions (EFs) of 1m-PFOS have been shown to be nonracemic, suggesting that PFOS-precursors are a significant source of PFOS in humans, but little is known about the importance of PFOS-precursors in ecosystems. In the current work, concentrations of PFOS, perfluorooctane sulfonamide (PFOSA), PFOS isomer profiles, and EFs of 1m-PFOS were determined in Lake Ontario water, sediment, fishes and invertebrates. Concentrations of PFOS and PFOSA were highest in slimy sculpin and Diporeia, and concentrations of the two compounds were often correlated. 1m-PFOS was racemic in sediment, water, sculpin and rainbow smelt, but nonracemic in the top predator, lake trout, and all invertebrate species. Furthermore, EFs were correlated with the relative concentrations of PFOS and PFOSA in invertebrates. Overall, these empirical observations with a new analytical tool confirm previous suggestions that PFOS-precursors contribute to PFOS in the food web, likely via sediment. Implications are that future PFOS exposures in this ecosystem will be influenced by an in situ source, and that the apparent environmental behavior of PFOS (e.g., bioaccumulation potential) can be confounded by precursors.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.234
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0010.004
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.025
GPT teacher head0.283
Teacher spread0.258 · 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

Citations70
Published2012
Admission routes3
Has abstractyes

Explore more

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