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Record W1926944406 · doi:10.1139/as-2015-0004

Mercury concentrations in multiple tissues of Arctic Iceland Gulls (<i>Larus glaucoides</i>) wintering in Newfoundland

2015· article· en· W1926944406 on OpenAlexafffundvenueabout
Alexander L. Bond, Gregory J. Robertson

Bibliographic record

VenueArctic Science · 2015
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsEnvironment and Climate Change Canada
FundersMemorial University of Newfoundland
KeywordsFeatherLarusArcticMercury (programming language)BreedThe arcticGeographyMERCURY EXPOSUREBiologyZoologyFisheryEcologyHerringOceanographyBiomonitoring

Abstract

fetched live from OpenAlex

Anthropogenic mercury (Hg) emissions are increasing and are potentially of concern for Arctic-nesting seabirds, particularly those that spend part of their year near dense human habitation. Iceland Gulls (Larus glaucoides B. Meyer, 1822) breed in the eastern Canadian Arctic and spend the majority of winter in towns and cities in eastern Newfoundland. We measured Hg in breast feathers, blood plasma, and red blood cells of Iceland Gulls wintering in and around St. John's, Newfoundland and Labrador, from 2011 to 2014. Mercury in blood plasma comprised &lt;10% of the total blood Hg. We found no difference in red blood cell Hg between first-winter and adult birds, which likely reflects their similar feeding habits. Feather Hg in adults was significantly greater than that in first-winter birds because adults had accumulated a greater body Hg burden to excrete (up to a year, compared with a few months' accumulation in first-winter birds). Overall, concentrations were among the lowest found for Larus spp. and Arctic gulls, suggesting that Hg does not pose a risk to Iceland Gulls at the present.

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)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.019
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.040
GPT teacher head0.288
Teacher spread0.249 · 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 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

Citations16
Published2015
Admission routes4
Has abstractyes

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