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Record W1979932482 · doi:10.1039/c0em00154f

Temporal trends of contaminants in Arctic char (Salvelinus alpinus) from a small lake, southwest Greenland during a warming climate

2010· article· en· W1979932482 on OpenAlex
Frank F. Rigét, Katrin Vorkamp, Derek C. G. Muir

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Environmental Monitoring · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsEnvironment and Climate Change Canada
FundersNational Research Council CanadaMiljøstyrelsen
KeywordsArctic charSalvelinusArcticEnvironmental scienceOceanographyThe arcticEcologyClimate changeCharFisheryGeologyGeographyFish <Actinopterygii>BiologyArchaeologyTrout

Abstract

fetched live from OpenAlex

Hg and legacy POPs were analysed in muscle tissue of a landlocked Arctic char (Salvelinus alpinus) population from a small lake in southwest Greenland. Hg concentrations were available for six years and OC concentrations for five years during the period 1994 to 2008. For two years, stable isotope values of nitrogen (δ(15)N) were analysed in muscle tissue in order to infer trophic effects. Hg, Σ10-PCB, ΣDDT and trans-nonachlor concentrations (OC on wet weight basis) showed an increase with increasing fish length, which had to be accounted for when assessing temporal trends. δ(15)N values had a narrow range, and there was no indication of increasing δ(15)N values with char length confirming the sampled char did not vary in trophic morphs as often seen in Arctic lakes. Length-adjusted Hg concentrations showed a significantly increasing trend during the period 1994 to 2008, while Σ10-PCB, ΣDDT, ΣHCH and trans-nonachlor showed a significantly decreasing trend when expressed on wet weight, and decreasing but not significantly when expressed on lipid weight. The reason for this was that the lipid content of muscle showed a significantly decreasing trend with time. The sum of mean monthly air temperature during May to August measured at a nearby meteorological station showed an increasing trend during the study period, and changing temperature conditions probably influenced the temporal trend of especially Hg concentrations and the lipid content.

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.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.247
Threshold uncertainty score0.737

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 head0.015
GPT teacher head0.242
Teacher spread0.226 · 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