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Record W342848614 · doi:10.2166/wqrj.2009.028

Perfluorinated Alkyl Acid Concentrations in Canadian Rivers and Creeks

2009· article· en· W342848614 on OpenAlexafffundabout
Brian F. Scott, Christine Spencer, Emma López, Derek C. G. Muir

Bibliographic record

VenueWater Quality Research Journal · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicPer- and polyfluoroalkyl substances research
Canadian institutionsEnvironment and Climate Change Canada
FundersManitoba Hydro
KeywordsPerfluorooctanoic acidPerfluorooctaneEnvironmental chemistryAlkylSulfonatePopulationEnvironmental scienceChemistryEnvironmental healthOrganic chemistryMedicine

Abstract

fetched live from OpenAlex

Abstract Perfluorinated alkyl acids (PFAs) belong to a family of chemicals that are highly persistent and potentially ecotoxic. They are under scrutiny by government agencies who must determine their risk to humans and the environment. Numerous studies have measured perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) in selected areas of the world, but there has been no systematic cross-Canada study of these compounds in surface waters. This report describes the concentrations of PFAs in 38 rivers across Canada (42 to 60°N and 62 to 136°W). Samples were collected upstream and downstream of populated areas. PFOS and PFOA were the predominant PFAs detected. Values of PFOS ranged from <0.020 to 34.6 ng/L and PFOA ranged from 0.044 to 9.9 ng/L. Highest concentrations occurred in areas of high population densities, generally at downstream sites. The shorter chain perfluorocarboxylates (PFCAs) (C6)to C9) were present in most samples but the longer chain PFCAs (C10 to C14) were not often detected. Perfluorohexane sulfonate was the next most frequently detected perfluoroalkylsulfonate while perfluoro-1-octanesulfonamide (PFOSA) was detected infrequently.

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 score0.037
Threshold uncertainty score0.095

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.001
Scholarly communication0.0020.000
Open science0.0010.000
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 head0.081
GPT teacher head0.392
Teacher spread0.311 · 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

Citations37
Published2009
Admission routes3
Has abstractyes

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