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Record W1965143380 · doi:10.1002/etc.5620191215

Comparison of polycyclic aromatic hydrocarbon and polychlorinated biphenyl dynamics in benthic invertebrates of Lake Erie, USA

2000· article· en· W1965143380 on OpenAlexaff
Sarah B. Gewurtz, Rodica Lazăr, G. Douglas Haffner

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2000
Typearticle
Languageen
FieldEnvironmental Science
TopicToxic Organic Pollutants Impact
Canadian institutionsUniversity of Windsor
Fundersnot available
KeywordsPolychlorinated biphenylBenthic zoneInvertebratePolycyclic aromatic hydrocarbonBiphenylEnvironmental chemistryEnvironmental scienceEcologyChemistryBiology

Abstract

fetched live from OpenAlex

Abstract hedistributionpatternsofpolycyclicaromatichydrocarbons(PAH)andpolychlorinatedbiphenyls(PCBs) were determined in four benthic invertebrate species of western Lake Erie, USA, to assess and compare the processes governing the exposure dynamics of these two classes of contaminants. Significant differences in the sum of 17 PAH compounds were observed among the four species, with mayflies containing the highest PAH body burden, followed by dreissenid mussels, amphipods, and crayfish. For PCBs, mayflies contained significantly higher concentrations of the sum of 39 PCB congeners than the other organisms, and dreissenids had higher levels than crayfish. No significant differences were found in the SPCB levels between dreissenids and amphipods or between amphipods and crayfish. For PCBs, the relationship between biota-sediment accumulation factors (BSAFs) and log Kow followed a parabolic pattern indicative of selective bioaccumulation. In contrast, BSAFs for PAHs were inversely related to log Kow, suggesting that metabolism of the higher Kowcompounds was occurring. These results support the conclusion that mayflies and dreissenids play major roles in the transfer of PAHs and PCBs to upper trophic levels, and they demonstrate that the exposure dynamics of PAHs and PCBs are different in the benthic components of aquatic food webs.

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 score0.069
Threshold uncertainty score0.995

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)0.0060.000

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 head0.225
Teacher spread0.219 · 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

Citations88
Published2000
Admission routes1
Has abstractyes

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