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Record W2125775031 · doi:10.1897/06-402r.1

Tracing salmon-derived nutrients and contaminants in freshwater food webs across a pronounced spawner density gradient

2007· article· en· W2125775031 on OpenAlexaff
Irene Gregory‐Eaves, Marc J. Demers, Lynda E. Kimpe, Eva M. Krümmel, Robie W. Macdonald, Bruce P. Finney, Jules M. Blais

Bibliographic record

VenueEnvironmental Toxicology and Chemistry · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsFisheries and Oceans CanadaMcGill UniversityUniversity of Ottawa
Fundersnot available
KeywordsFish migrationOncorhynchusRainbow troutNutrientFood webFisheryBiologySalmonidaeSalmoDeltaTroutEcologyFood chainEnvironmental scienceFish <Actinopterygii>Trophic level

Abstract

fetched live from OpenAlex

Many have demonstrated that anadromous Pacific salmon are significant vectors of nutrients from the ocean to freshwaters. Recently. however, it has been recognized that salmon spawners also input significant quantities of contaminants. The objectives of this paper are to delineate the extent to which salmon-derived nutrients are integrated into the freshwater food web using delta(15)N and delta(13)C and to assess the influence of the salmon pathway in the accumulation of contaminants in rainbow trout (Oncorhynchus mykiss). We found that the delta(15)N and delta(13)C of food web components were related positively and significantly to sockeye salmon (Oncorhynchus nerka) spawner density. Contaminant concentrations in rainbow trout also positively and significantly were related to sockeye salmon spawner density. These data suggest that the anadromous salmon nutrient and contaminant pathways are related and significantly impact the contaminant burden of resident fish.

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 score0.010
Threshold uncertainty score0.020

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)0.0000.000

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 head0.006
GPT teacher head0.204
Teacher spread0.198 · 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

Citations40
Published2007
Admission routes1
Has abstractyes

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