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Record W2318739473 · doi:10.1021/es303716k

Part I. A Temporal Study of PFCAs and Their Precursors in Human Plasma from Two German Cities 1982–2009

2013· article· en· W2318739473 on OpenAlexaff
Leo W. Y. Yeung, Shona Robinson, Jan Koschorreck, Scott A. Mabury

Bibliographic record

VenueEnvironmental Science & Technology · 2013
Typearticle
Languageen
FieldEnvironmental Science
TopicPer- and polyfluoroalkyl substances research
Canadian institutionsUniversity of Toronto
FundersNational Institute of Standards and Technology
KeywordsGermanHuman plasmaChemistryEnvironmental scienceEnvironmental chemistryEngineeringGeographyChromatographyArchaeology

Abstract

fetched live from OpenAlex

A total of 420 human plasma samples from two cities (Halle and Münster, Germany), collected between 1982 and 2009, were analyzed for a suite of PFCAs (C6-C12) and selected PFCA precursors (4:2-, 4:2/6:2-, 6:2-, 6:2/8:2-, 8:2-, 8:2/10:2-, and 10:2-diPAPs). PFCAs (C7-C11 and C13) were detected in over 80% of the samples (<0.005-39.4 ng/mL), while C12 PFCA was detected in fewer than 10% of the samples. In a range of 10-46% of the samples, 4:2-, 4:2/6:2-, 6:2, and 8:2-diPAPs were identified at concentrations of <0.0002-0.687 ng/mL; fewer than 10% of the samples had detectable 10:2-diPAP. Temporal trends (2000-2009) showed increasing concentrations of PFNA, PFDA, and PFUnDA, whereas PFOA concentrations were decreasing. Calculated population halving time for PFOA varied between 8.2-14.5 years, which contrasts to the generally accepted value of 3.8 years. This suggests an ongoing or additional exposure to PFOA or one of its precursor compounds. DiPAPs, known to metabolize rapidly to PFCAs, were detected in a significant number of samples and at concentrations that have not declined significantly over the past half-decade. The evidence suggests they have contributed to the continued presence of the longer chain PFCAs and perhaps contribute to the slow decline of PFOA.

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 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 score0.121
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.004
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.011
GPT teacher head0.261
Teacher spread0.250 · 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

Citations113
Published2013
Admission routes1
Has abstractyes

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