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Record W2008231304 · doi:10.1155/2009/275040

Trace Element Concentrations in Bearded Seals (<i>Erignathus barbatus</i>) Near Red Dog Mine Compared to Other Locations in Alaska

2009· article· en· W2008231304 on OpenAlexaboutno aff
Lori Quakenbush, John J. Citta

Bibliographic record

VenueJournal of Marine Biology · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsnot available
FundersNational Marine Fisheries ServiceNational Oceanic and Atmospheric AdministrationNational Science Foundation
KeywordsTrace elementArsenicCadmiumBayMercury (programming language)SeleniumBiologyArchaeologyChemistryGeography

Abstract

fetched live from OpenAlex

To determine if bearded seals ( Erignathus barbatus ) harvested near a zinc and lead mine (Red Dog, Alaska , USA) by subsistence hunters from Kivalina, Alaska, were as safe to eat as bearded seals from other locations in Alaska, we compared 19 trace element concentrations in liver tissue. Liver concentrations from nine bearded seals harvested near the Red Dog Mine (RDM) port site were compared with 15 bearded seals from two reference sites (Hooper Bay and Little Diomede, Alaska, USA). Concentrations did not differ by gender, but we found statistically significant trends in concentrations of cadmium, mercury, manganese, selenium, and vanadium with age. Arsenic and copper were the only elements found to be more concentrated in the liver of bearded seals harvested near RDM than in the other locations. The predominant form of arsenic in marine mammals is known to be a nontoxic organic form, not the toxic inorganic form, and copper is an essential element. Although elevated near RDM, neither element was found at concentrations that presented health risks. We found no evidence that bearded seals harvested near RDM were less safe to eat or that trace element concentrations were greater than those found in bearded seals harvested elsewhere in Alaska or Canada.

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 score0.031
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)0.0010.000

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 head0.294
Teacher spread0.276 · 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

Citations20
Published2009
Admission routes1
Has abstractyes

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