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Record W4226461644 · doi:10.1007/s00244-022-00922-x

Perfluoroalkyl Substances (PFASs) in the Canadian Freshwater Environment

2022· article· en· W4226461644 on OpenAlexaffabout
Benoit A. Lalonde, Christine Garron

Bibliographic record

VenueArchives of Environmental Contamination and Toxicology · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicPer- and polyfluoroalkyl substances research
Canadian institutionsEnvironment and Climate Change Canada
Fundersnot available
KeywordsPerfluorooctanoic acidPerfluorooctaneEnvironmental chemistryTrophic levelEcotoxicologyEnvironmental scienceChemistryEcologySulfonateBiologyOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Per- and polyfluoroalkyl substances (PFASs) are anthropogenic substances that are very stable in the receiving environment. Legacy perfluoroalkane sulfonates (PFSAs) and perfluoroalkyl carboxylic acids (PFCAs) are especially persistent and resistant to typical environmental degradation processes and therefore are distributed across all trophic levels and environmental compartments (soil, air, water). Since most uses of perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), and LC-long-chain PFCAs are banned in Canada, alternative PFASs have been in use for a number of years. Twenty-nine sites across Canada were sampled for PFASs to determine concentrations and trends. Overall, 13 PFASs were measured in 566 Canadian freshwater samples from 2013 to 2020 with a range from below the detection limit (LOD range: 0.4–1.6 ng/L) of the laboratory to a maximum of 138 ng/L (for PFBS). While PFOS and PFOA concentrations are declining significantly over time, other compounds such as PFPeA and PFBA have increased significantly over 2013–2020. Overall, the range of concentrations found in this study was similar to that of other Canadian and international studies. However, this study also found a higher frequency of detections of the replacement PFASs than that of the other, older, Canadian studies.

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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.286
Threshold uncertainty score1.000

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)0.0090.000

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 head0.217
Teacher spread0.207 · 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

Citations38
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueArchives of Environmental Contamination and ToxicologySame topicPer- and polyfluoroalkyl substances researchFrench-language works237,207