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Record W4405592564 · doi:10.1016/j.ecoenv.2024.117561

Exposure pathways (diet, dissolved or particulate substrate) of rare earth elements to aquatic organisms

2024· article· en· W4405592564 on OpenAlexafffund
Ashlyn Kernaghan, Duc Huy Dang

Bibliographic record

VenueEcotoxicology and Environmental Safety · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeochemistry and Elemental Analysis
Canadian institutionsTrent University
FundersNatural Sciences and Engineering Research Council of CanadaTrent University
KeywordsParticulatesEnvironmental chemistrySubstrate (aquarium)Rare earthAquatic ecosystemEnvironmental scienceChemistryEcologyBiologyMineralogy

Abstract

fetched live from OpenAlex

The global extraction and use of rare earth elements (REEs) continue to rise as they are implemented in technologies that improve human and environmental livelihoods. However, the general understanding of transfer processes and fates of REEs in aquatic systems remains limited. Here, we aim to determine the REEs' main exposure pathways, e.g., particulate fraction, diet, or dissolved (ionic) fractions, to three benthic and three pelagic organisms. They were maintained under laboratory conditions and exposed to natural river water , with or without a sand substrate and an adapted diet. The organisms include northern clearwater crayfish ( Faxonius propinquus ), chinese mystery snail ( Cipangopaludina chinensis ), black sandshell mussel (Ligumia recta ), striped shiner minnows ( Luxilus chrysocephalus ), Daphnia magna , and Euglena gracilis . The combined results of REE concentrations, fractionations, and anomalies highlighted that pelagic organisms are characterized by heavy REEs enrichment indicating they mainly uptake REEs in the dissolved form with high bioaccumulation potential, i.e., bioconcentration (BCF) > 1 and diet accumulation factors (DAF) < 1. Pelagic organisms exhibited relatively low REE concentrations in their tissues ([La] ranging from 4.6 to 57.7 µg kg −1 in minnows, 18.4 µg kg −1 in whole body D. magna , and 32.2 µg kg −1 in E. gracilis ). On the other hand, snails and mussels were enriched in light REEs showing they mainly uptake REEs through their respective diets and particulate sand substrate. Relative to pelagic organisms, mussels and snails have higher DAFs (161.2 and 18.6, respectively) and REE levels in their soft tissues ([La] of 5700 µg kg −1 and 650 µg kg −1 , respectively), but DAF for crayfish remains < 1. In summary, under environmental-relevant conditions, the six aquatic organisms has the potential to accumulate REEs through various uptake pathways. Nevertheless, our results confirming preferential uptake pathways of the six organisms can help select appropriate species in future studies to monitor REE exposure from vaious fractions: dissolved, particulate forms or in the food webs (i.e., diet).

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

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)0.0010.000

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 head0.009
GPT teacher head0.190
Teacher spread0.180 · 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 designBench or experimental
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

Citations6
Published2024
Admission routes2
Has abstractyes

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