MétaCan
Menu
Back to cohort
Record W2046045680 · doi:10.1897/08-557.1

Mercury concentrations in Southern Beaufort Sea polar bears: Variation based on stable isotopes of carbon and nitrogen

2009· article· en· W2046045680 on OpenAlexaboutno aff
Tamara Cardona‐Marek, Katrina K. Knott, Benjamin E. Meyer, Todd M. O’Hara

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2009
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine animal studies overview
Canadian institutionsnot available
FundersNational Center for Research Resources
KeywordsUrsus maritimusMercury (programming language)Methylmercuryδ15NTrophic levelBeaufort seaPelagic zoneChemistryStable isotope ratioBenthic zoneδ13CEnvironmental chemistryPolar nightEcologyZoologyBiologyArcticBioaccumulation

Abstract

fetched live from OpenAlex

Total Hg concentration was measured in hair and whole blood of 52 adult Southern Beaufort Sea polar bears (Ursus maritimus) captured in the spring of 2005. Stable isotopic signatures (i.e., 13C/12C, delta13C; 15N/14N, delta15N) in hair and two blood compartments (packed blood cells/clot and serum) were determined to assess the variation of Hg concentrations among polar bears in relation to their feeding ecology and other biological factors. Concentrations of Hg in hair and blood (2.2-23.9 microg/g dry wt and 0.007-0.213 microg/g wet wt, respectively) were within the range of values previously reported for polar bears in Canada and East Greenland. Mercury concentration in hair from females was higher than that in hair from males, and concentration was related to interactions between delta13C, delta15N, and longitude of capture location. Mercury concentrations in hair were inversely correlated to delta13C in hair and blood, suggesting that polar bears with greater total Hg concentrations fed more on pelagic prey, such as ringed seals or beluga whale, than on benthic prey. Variability in Hg concentrations in polar bear hair and blood may be the result of intraspecific or regional variation in prey selection rather than strictly trophic level interactions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

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 head0.006
GPT teacher head0.196
Teacher spread0.190 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations62
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueEnvironmental Toxicology and ChemistrySame topicMarine animal studies overviewFrench-language works237,207