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Record W2559269211 · doi:10.5539/enrr.v6n4p125

Antifouling Effectiveness and Potential Toxicological Risk of an Elastomer-Based Coating against Zebra Mussels

2016· article· en· W2559269211 on OpenAlexaffvenue
Yves de Lafontaine, Julie Veillette

Bibliographic record

VenueEnvironment and Natural Resources Research · 2016
Typearticle
Languageen
FieldEngineering
TopicMarine Biology and Environmental Chemistry
Canadian institutionsEnvironment and Climate Change CanadaFisheries and Oceans Canada
Fundersnot available
KeywordsBiofoulingDreissenaCoatingEnvironmental scienceEnvironmental chemistryZebra musselBarnacleBiocideFoulingFreshwater ecosystemMusselEcosystemChemistryEcologyBivalviaMaterials scienceBiologyMolluscaNanotechnologyCrustacean

Abstract

fetched live from OpenAlex

The fouling of hard substrates by zebra mussels (Dreissena sp.) in freshwater ecosystems is a persistent problem which calls for antifouling treatments being fully efficient, long-lasting, and environmentally safe. The present study assessed the potential toxicological impact and the effectiveness of an elastomer-based coating containing salts that would make surfaces repulsive to zebra mussel attachment. Laboratory testing using standard analytical methods for water and wastewater, and a battery of six bioassays confirmed that the leachates from the coating exhibited no toxic response suggesting its safety to the receiving environment. In situ experiments using multi-plate collectors indicated that biofouling by zebra mussels and sponges on coated surfaces was effectively reduced by up to 97% over one growing season. Effectiveness of the coating was slightly less (82%) during the second growing season. Results suggested that the repulsive effect would be due to the presence of salts within the elastomer-based coating affecting both zebra mussels and other freshwater organisms. Saltwater experiments indicated that the coating was totally ineffective to prevent biofouling in marine environments. In addition of being environmentally safe to use, results suggested that the coating can be an effective antifouling product for submerged structures in freshwater environments.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.666
Threshold uncertainty score0.383

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 studies0.0000.000
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 head0.010
GPT teacher head0.244
Teacher spread0.234 · 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 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

Citations1
Published2016
Admission routes2
Has abstractyes

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