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Development of the cultivation of <i>Laminaria Saccharina</i> as the extractive inorganic component of an integrated aquaculture system and monitoring of therapeutants and phycotoxins

2003· article· en· W1968781924 on OpenAlexaffabout
Thierry Chopin, S. Bastarache, Ellen Belyea, K. Haya, DH Sephton, Jennifer L. Martin, Stephen Eddy, Ian J. Stewart

Bibliographic record

VenueJournal of Phycology · 2003
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicMarine and coastal plant biology
Canadian institutionsCanadian Food Inspection AgencyFisheries and Oceans CanadaUniversity of New Brunswick
Fundersnot available
KeywordsAquacultureLaminariaBiologySaccharinaKelpFisherySporophyteAlgaeEcologyBotany

Abstract

fetched live from OpenAlex

The development of sustainable integrated aquaculture systems requires combining fed aquaculture (finfish) with extractive inorganic aquaculture (seaweed) and extractive organic aquaculture (shellfish). With the support of AquaNet, the Network of Centers of Excellence in Aquaculture in Canada, we are developing such a system at an industrial pilot scale by co‐cultivating salmon (Salmo salar), kelp ( Laminaria saccharina ) and blue mussel ( Mytilus edulis ) at aquaculture sites in the Bay of Fundy, Canada. This presentation will focus on the development of the extractive inorganic component. The entire cycle of rearing Laminaria saccharina has been completed and improved, both in the laboratory and at the integrated sites: release in the laboratory of spores from mature macroscopic sporophytes, seeding of ropes, germination of microscopic gametophytes, sexual maturation of male and female gametophytes, development of zygotes into juvenile sporophytes, which are then transplanted to the sites for rapid grow‐out. Another aspect of the project, food safety monitoring of chemical therapeutants and phycotoxins in mussel and kelp cultured in proximity to salmon, will also be described. The productivity, nutrient absorption capacity, and role of the seaweed component are being analyzed so that its appropriate scale to the other components can be defined in order to develop responsible aquaculture practices in which metabolic/physiological processes of the different co‐cultured organisms counter‐balance each other within acceptable operational limits. Adopting polytrophic strategies will be key to the aquaculture industry to develop its environmentally and economically‐balanced diversification and increase its social acceptability within a broader coastal management framework.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.336
Threshold uncertainty score0.167

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.014
GPT teacher head0.222
Teacher spread0.208 · 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 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

Citations6
Published2003
Admission routes2
Has abstractyes

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