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Record W4391969650 · doi:10.1007/s11356-024-32268-3

Contrasting trophic transfer patterns of cadmium and mercury in the Arctic marine food web of east Hudson Bay, Canada

2024· article· en· W4391969650 on OpenAlexafffundabout
Jillian Rohonczy, John Chételat, Stacey A. Robinson, Lucassie Arragutainaq, Joel P. Heath, Christine McClelland, Raymond Mickpegak, Mark R. Forbes

Bibliographic record

VenueEnvironmental Science and Pollution Research · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsMakivik CorporationThe Arctic Eider SocietyEnvironment and Climate Change CanadaCarleton University
FundersNorthern Contaminants ProgramCrown-Indigenous Relations and Northern Affairs CanadaEnvironment and Climate Change Canada
KeywordsTrophic levelFood webBiomagnificationBayEiderBioaccumulationCadmiumMercury (programming language)ArcticFood chainWeaselEcologyBiologyPredationOceanographyChemistry

Abstract

fetched live from OpenAlex

We investigated trophic transfer of cadmium (Cd) through an Arctic marine food web in Hudson Bay and compared it with mercury (Hg), a metal known to strongly biomagnify. We evaluated blue mussel, sea urchin, common eider, sculpin, Arctic cod, and ringed seal for the influence of dietary and biological variables on variation in Cd and Hg concentrations. Age and size influenced metal concentrations among individuals within a vertebrate species. Consumer carbon and sulfur isotope values were correlated with their Cd and Hg concentrations, indicating habitat-specific feeding influenced metal bioaccumulation. Trophic transfer patterns for Cd depended on the vertebrate tissue, with food web biodilution observed for the muscle but not the liver. Liver Cd concentrations were higher in ringed seal and some common eider relative to prey. In contrast, we observed mercury biomagnification for both tissues. Tissue- and species-specific physiology can explain discrepancies of Cd trophic transfer in this Arctic marine food web.

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)0.001
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 score0.100
Threshold uncertainty score0.201

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
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 head0.029
GPT teacher head0.279
Teacher spread0.250 · 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

Citations8
Published2024
Admission routes3
Has abstractyes

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