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Record W2788684252 · doi:10.1139/facets-2017-0086

Mercury exposure to red-winged blackbirds (<i>Agelaius phoeniceus</i>) and dragonfly (Odonata: Aeshnidae) nymphs in Prairie Pothole wetlands

2018· article· en· W2788684252 on OpenAlexaffvenue
Jared D. Wolfe, Oksana P. Lane, R. Mark Brigham, Britt D. Hall

Bibliographic record

VenueFACETS · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsOdonataFeatherDragonflyWetlandNymphBiologyMethylmercuryEcologyMercury (programming language)WildlifeLibellulidaeZoologyBioaccumulation

Abstract

fetched live from OpenAlex

The Prairie Pothole Region (PPR) in the northern Great Plains is an area of ecological significance, serving as an important breeding site for avian wildlife. However, organisms feeding within the PPR may be at risk of mercury (Hg) exposure due to deposition of anthropogenic emissions and the high Hg methylation potential of PPR wetlands. We quantified Hg concentrations in red-winged blackbirds’ ( Agelaius phoeniceus (Linnaeus, 1766); RWBLs) blood, feathers, and eggs in the spring and summer breeding season and compared our values with those from RWBLs sampled from ecoregions across North America. Hg concentrations in whole water, aeshnid dragonfly nymphs, and RWBL tissues varied by wetland and were below those considered to elicit acute effects in wildlife, and egg total Hg (THg) concentrations were significantly related to spring whole water methylmercury concentrations. Only RWBL blood THg concentrations showed a clear increase in summer compared with spring, resulting in decoupling of summer blood and feather THg concentrations. Moreover, blood THg concentrations varied by ecoregion, with those impacted by an industrial point source exhibiting high Hg levels. Our study emphasizes that tissue renewal time as well as ecological factors such as competition and diet shifts are important considerations when using RWBLs to assess biological Hg exposure.

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 score0.073
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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.013
GPT teacher head0.259
Teacher spread0.246 · 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

Citations5
Published2018
Admission routes2
Has abstractyes

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