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Record W2318034720 · doi:10.1021/es502720a

Microsatellite DNA Mutations in Double-Crested Cormorants (<i>Phalacrocorax auritus</i>) Associated with Exposure to PAH-Containing Industrial Air Pollution

2014· article· en· W2318034720 on OpenAlexafffundabout
Laura E. King, Shane R. de Solla, Jeff Small, Ed Sverko, James S. Quinn

Bibliographic record

VenueEnvironmental Science & Technology · 2014
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicGenetically Modified Organisms Research
Canadian institutionsEnvironment and Climate Change CanadaMcMaster University
FundersEnvironment CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsHarbourCormorantPollutionMicrosatelliteContaminationBiologyEnvironmental chemistryEnvironmental scienceEcologyChemistryGeneticsGenePredation

Abstract

fetched live from OpenAlex

Hamilton Harbour, Ontario, Canada is one of the most polluted sites on the Great Lakes, and is subject to substantial airborne pollution due to emissions from both heavy industry and intense vehicle traffic. Mutagenic Polycyclic aromatic hydrocarbons (PAHs) are present at very high concentrations in the air and sediment of Hamilton Harbour. We used five variable DNA microsatellites to screen for mutations in 97 families of Double-crested Cormorants (Phalacrocorax auritus) from three wild colonies, two in Hamilton Harbour and one in cleaner northeastern Lake Erie. Mutations were identified in all five microsatellites at low frequencies, with the majority of mutations found in chicks from the Hamilton Harbour site closest to industrial sources of PAH contamination. Microsatellite mutation rates were 6-fold higher at the Hamilton Harbour site closest to the industrial sources of PAH contamination than the other Hamilton Harbour site, and both were higher than the reference colony. A Phase I metabolite of the PAH benzo[a]pyrene identified by LC-MS/MS in bile and liver from Hamilton Harbour cormorant chicks suggests that these cormorants are exposed to and metabolizing PAHs, highlighting their potential to have caused the observed mutations.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.698
Threshold uncertainty score0.427

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.003
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.018
GPT teacher head0.222
Teacher spread0.203 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations19
Published2014
Admission routes3
Has abstractyes

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