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Record W4401893634 · doi:10.3389/fenvs.2024.1439573

Investigating the ecological and toxicological significance of Cyanox®53 recovered from intertidal sediments and varnish clam

2024· article· en· W4401893634 on OpenAlexafffund
Stephanie L. Renkers, Leah Bendell

Bibliographic record

VenueFrontiers in Environmental Science · 2024
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsSimon Fraser University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsIntertidal zoneEcologyEnvironmental scienceVarnishMolluscaInvertebrateEnvironmental chemistryGastropodaBiologyChemistry

Abstract

fetched live from OpenAlex

We examined the ecological and toxicological implications of the microplastic, Cyanox ® 53, found in sediments and varnish clams across seven beaches in Burrard Inlet, British Columbia (BC). Using the simulation models embedded within Estimation Programs Interface (EPI) Suite™, the potential persistence, bioaccumulation, and toxicity of Cyanox ® 53 was assessed to evaluate the risk to varnish clams foraging on sediment containing this contaminant. Moreover, we used a bioenergetic model, based on the blue-listed surf scoter species, to estimate the risk of daily ingestion of Cyanox ® 53 per body weight in overwintering seabirds. Our findings indicate that varnish clams collected from Burrard Inlet accumulate on average 0.46 particles of Cyanox ® 53/clam, and based on bioenergetic modeling, results in surf scoters potentially consuming 78 (for males) to 83 (for females) pieces of Cyanox ® 53 daily from foraged varnish clams. EPI Suite™ predicted Cyanox ® 53 to be persistent, however, unlikely to bioaccumulate as a “traditional” chemical. Furthermore, the estimation of potential acute and chronic toxicity of Cyanox ® 53 to aquatic organism surrogates, such as fish, Daphnia magna , and green algae, was inconclusive due to model variability and limitations within EPI Suite™. To fully understand the potential risks of Cyanox ® 53 further investigation is warranted.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.535
Threshold uncertainty score1.000

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 studies0.0000.003
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 head0.008
GPT teacher head0.199
Teacher spread0.191 · 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.

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

Citations2
Published2024
Admission routes2
Has abstractyes

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