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Record W4285155027 · doi:10.3354/aei00434

Modeling the effect of cage drag on particle residence time within fish farms in the Bay of Fundy

2022· article· en· W4285155027 on OpenAlex

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.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueAquaculture Environment Interactions · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsBedford Institute of OceanographyFisheries and Oceans Canada
Fundersnot available
KeywordsBayDragResidence time (fluid dynamics)Environmental scienceCageDrag coefficientFlow (mathematics)FisheryAquacultureBathymetryOceanographyAtmospheric sciencesFish <Actinopterygii>GeologyPhysicsMechanicsBiologyGeotechnical engineeringEngineering

Abstract

fetched live from OpenAlex

Aquaculture farm cages have the ability to interact with local circulation due to the drag caused by the cages. We examined how the drag influences the residence time of particles within fish farms in the southwest Isles region of New Brunswick, Canada, in the Bay of Fundy using a high-resolution hydrodynamic model. To accomplish this, we parameterized the cage drag in the model and modeled flow structures at multiple spatial scales, ranging from several meters within the cages, to tens of kilometers in the adjacent open ocean. We used models with and without cage drag to demonstrate how residence time was influenced by the imposition of the cage infrastructure. Our examination indicated that the drag produced by cages is able to significantly change the residence time of particles. The magnitude of the change is strongly sensitive to the timing of tides, tidal speeds and specific locations of farms. Our results suggest that the flushing properties of the wastes from aquaculture activities—for example, feed and subsequently fecal material—are strongly related to flow properties and their interactions with cages. These results emphasize that the design of fish farms should explicitly account for the influence of physical infrastructure (i.e. cages) on depositional processes in order to try and minimize environmental effects.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.614
Threshold uncertainty score0.998

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)0.0030.000

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 head0.011
GPT teacher head0.243
Teacher spread0.232 · 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