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Effects of nutrition on larval growth and survival in bivalves

2010· article· en· W2066407794 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueReviews in Aquaculture · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsUniversity of British ColumbiaVancouver Island UniversityFisheries and Oceans Canada
FundersFisheries and Oceans CanadaNatural Sciences and Engineering Research Council of Canada
KeywordsBiologyLarvaCrassostreaPacific oysterIchthyoplanktonAquaculturePhytoplanktonCarbohydrateAnimal scienceZoologyOysterFood scienceFisheryEcologyBiochemistryFish <Actinopterygii>Nutrient

Abstract

fetched live from OpenAlex

Abstract This review examines the nutritional factors that influence the growth and survival of larval bivalves. Factors considered include feed form (live phytoplankton, preserved phytoplankton and artificial feeds) and feed biochemical composition (protein, lipid, carbohydrate and essential fatty acids). These factors, as they relate to larval production, are discussed in terms of growth and survival rates. To facilitate comparisons among larval studies, growth rates and feeding rates are standardized to common units. In addition, the standardized results for larvae of the Pacific oyster ( Crassostrea gigas Thunberg) are analysed using linear regression techniques to determine the strength of the correlations between daily doses of biochemical feed components and daily growth rates. Piecewise linear spline modelling is used to determine maximum effective dose response, the point where feeding additional biochemical components to the larvae yields no significant improvements in growth. Derived from these analyses are suggested daily rations of lipid, protein, carbohydrate, eicosapentanoic acid, docosahexanoic acid and energy for larvae of C. gigas .

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.390
Threshold uncertainty score0.432

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 head0.008
GPT teacher head0.255
Teacher spread0.246 · 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