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Record W2149701393 · doi:10.7589/0090-3558-38.4.706

MERCURY IN BALD EAGLE NESTLINGS FROM SOUTH CAROLINA, USA

2002· article· en· W2149701393 on OpenAlexfundno aff
Charles H. Jagoe, A. Lawrence Bryan, Heather A. Brant, Thomas M. Murphy, I. Lehr Brisbin

Bibliographic record

VenueJournal of Wildlife Diseases · 2002
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
FundersNational Research Council CanadaUniversity of GeorgiaU.S. Department of Energy
KeywordsMercury (programming language)Bald eagleMERCURY EXPOSUREFledgeBiologyFeatherAccipitridaeEagleDry weightFisheryZoologySouth carolinaPredationEcologyAnimal scienceBiomonitoring

Abstract

fetched live from OpenAlex

Bald eagles (Haliaeetus leucocephalus) may be at risk from contaminants in their diet and young birds may be particularly sensitive to contaminant exposure. To evaluate potential risks from dietary mercury exposure to eagle nestlings in South Carolina (USA), we surveyed mercury concentrations in 34 nestlings over two breeding seasons (1998 and 1999). Samples were also obtained from several post-fledging eagles in the region. Nestling feather mercury ranged from 0.61-6.67 micrograms Hg/g dry weight, nestling down mercury from 0.50-5.05 micrograms Hg/g dry weight, and nestling blood mercury from 0.02-0.25 microgram Hg/g wet weight. We did not detect significant differences in tissue mercury between nestlings from coastal and inland regions in contrast to some other studies of piscivorous birds. Mercury concentrations were much higher in the post fledging birds we sampled. Our data show that nestling eagles in South Carolina are accumulating mercury, and that concentrations in older birds may exceed regulatory guidelines.

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 score0.021
Threshold uncertainty score0.996

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)0.0050.000

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 head0.021
GPT teacher head0.242
Teacher spread0.220 · 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

Citations23
Published2002
Admission routes1
Has abstractyes

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