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Record W2054976852 · doi:10.1111/are.12380

The effectiveness of several commercial antifouling treatments at reducing biofouling on finfish aquaculture cages in British Columbia

2014· article· en· W2054976852 on OpenAlex
Courtney D. Edwards, Kylee A. Pawluk, Stephen F. Cross

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAquaculture Research · 2014
Typearticle
Languageen
FieldEngineering
TopicMarine Biology and Environmental Chemistry
Canadian institutionsUniversity of Victoria
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsBiofoulingAquacultureBiologyFoulingBiomass (ecology)Pulp and paper industryFisheryEcologyFish <Actinopterygii>Engineering

Abstract

fetched live from OpenAlex

Biofouling in finfish aquaculture is an important issue because copper based antifoulants contribute to marine pollution and biofouling management incurs heavy costs to the industry. The purpose of this study was to assess the effectiveness five treatments (non-biocidal: Dyneema, Netpolish, Aquacoating and ThornD; biocidal using cuprous oxide: Netrex) as compared with an untreated nylon net. After 8 months, effectiveness was determined by quantifying changes in: per cent net occlusion, per cent cover of major fouling groups, and biomass. Only one non-biocidal treatment performed better than the control in one performance index (Dyneema had lower biomass), and overall, the copper treatment was most effective. The results from this study demonstrated that the effectiveness of copper treatments will continue to be a barrier to the implementation of non-biocidal antifoulants, and that more research is needed to develop effective, non-biocidal antifoulant coatings for aquaculture operations.

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.

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 score0.284
Threshold uncertainty score0.997

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 integrity0.0000.001
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 head0.015
GPT teacher head0.270
Teacher spread0.255 · 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