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Record W2156665667 · doi:10.1139/f05-027

Evidence for biomagnification of rubidium in freshwater and marine food webs

2005· article· en· W2156665667 on OpenAlexfundvenueno aff
Linda M. Campbell, Aaron T. Fisk, Xiaowa Wang, Günter Köck, Derek C. G. Muir

Bibliographic record

VenueCanadian Journal of Fisheries and Aquatic Sciences · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicIsotope Analysis in Ecology
Canadian institutionsnot available
FundersNational Research Council CanadaMinistry of Environment
KeywordsBiomagnificationEnvironmental chemistryBioaccumulationTrophic levelFood webBiotaEcologyRubidiumBioconcentrationEnvironmental scienceChemistryBiologyPotassium

Abstract

fetched live from OpenAlex

Rubidium (Rb), a rarely studied alkali metal, may be an essential ultra-trace element for humans and other organisms. However, very little information exists in regard to the concentrations and distribution of Rb in freshwater and marine food webs. We measured Rb concentrations in freshwater fish from Lake Erie and two Arctic lakes (Lake Hazen and Resolute Lake) and in seabirds, ringed seals, and invertebrates from the marine Northwater Polynya in Baffin Bay. The alkali analogues of Rb, cesium (Cs), and potassium (K) were also analysed in a subset of fish from Lakes Erie and Hazen. Rb and Cs concentrations and Cs:K ratios in the sampled biota are significantly regressed against δ 15 N values, indicating biomagnification through the food web in diverse ecosystems. However, there is no relationship between K concentrations and δ 15 N values, indicating a lack of biomagnification and the presence of homeostatistic mechanisms for this essential trace element. Rb must be included with mercury and Cs as metals that consistently biomagnify in diverse food webs and should be considered in multi-element biomagnification studies.

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)0.000
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 score0.415
Threshold uncertainty score0.592

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
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 head0.036
GPT teacher head0.244
Teacher spread0.208 · 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

Citations103
Published2005
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Fisheries and Aquatic SciencesSame topicIsotope Analysis in EcologyFrench-language works237,207