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Record W2021843525 · doi:10.1021/es0628093

Determining Residence Patterns of Rainbow Trout Using Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS) Analysis of Selenium in Otoliths

2007· article· en· W2021843525 on OpenAlexaff
Vince Palace, Norman M. Halden, Panseok Yang, R. E. Evans, George Sterling

Bibliographic record

VenueEnvironmental Science & Technology · 2007
Typearticle
Languageen
FieldEnvironmental Science
TopicMercury impact and mitigation studies
Canadian institutionsUniversity of ManitobaFisheries and Oceans Canada
Fundersnot available
KeywordsRainbow troutSeleniumEnvironmental chemistryInductively coupled plasma mass spectrometryChemistryContaminationEffluentTroutEstuaryEnvironmental scienceFish <Actinopterygii>Mass spectrometryFisheryEcologyChromatographyBiologyEnvironmental engineering

Abstract

fetched live from OpenAlex

Toxicological studies are often hampered by concerns of fish residency in the industrial effluent being evaluated. Contaminants in muscle or visceral tissue are useful indicators of recent exposure, but depuration, metabolic transformation, and tissue recompartmentalization of contaminants makes their use as temporal markers tenuous. Otoliths are metabolically stable and can provide temporal resolution for exposure to some elements that are incorporated into their calcified structure, including the divalent cations Sr, Zn, and Mn. Here we provide the first determinations of selenium, an anion in biological systems, in the otoliths of rainbow trout captured from a site receiving runoff with elevated selenium from a coal mine operation. Concentrations of selenium in annual growth zones of otoliths suggest that fish from the mine-impacted system are recent immigrants from nearby reference streams not receiving selenium-bearing effluent.

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 score0.146
Threshold uncertainty score0.774

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0000.002
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 head0.014
GPT teacher head0.268
Teacher spread0.254 · 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

Citations54
Published2007
Admission routes1
Has abstractyes

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