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Effects of stocking density and substratum on the survival, growth, burrowing behaviour and shell morphology of juvenile basket cockle, Clinocardium nuttallii: implications for nursery seed production and field outplanting

2010· article· en· W1940487474 on OpenAlexaffabout
Anya Epelbaum, Christopher M. Pearce, Simon Yuan, Nadia Plamondon, Helen Gurney‐Smith

Bibliographic record

VenueAquaculture Research · 2010
Typearticle
Languageen
FieldEnvironmental Science
TopicMarine Bivalve and Aquaculture Studies
Canadian institutionsShell (Canada)Fisheries and Oceans CanadaVancouver Island University
Fundersnot available
KeywordsCockleBiologyStockingJuvenileSowingBroodstockAnimal scienceHatcheryFisheryAquacultureEcologyAgronomyFish <Actinopterygii>

Abstract

fetched live from OpenAlex

The basket cockle, Clinocardium nuttallii, is a candidate species for aquaculture in British Columbia, Canada. Previous research on broodstock conditioning, embryonic development and larval rearing of C. nuttallii demonstrated the potential for reliable hatchery production of cockle seed. In this paper, we investigated the effects of culture density (50% and 150% bottom cover in a monolayer) and substratum (none and fine sand) on cockle seed survival, growth, behaviour and shell morphology to improve the efficiency of the nursery production phase. Low stocking density (50% cover) yielded a shell length increase from 3 to 7 mm over a 4-week period. High stocking density (150% cover) negatively impacted some of the growth and condition parameters studied, but did not have a statistically significant effect on seed survival. Growing seed without substratum did not significantly affect seed survival or growth, but led to shell deformities (at shell length >15 mm) and lower burrowing rates when cockles were subsequently placed on sand. We recommend planting seed for grow-out at a shell length not exceeding 15 mm. Acclimating seed to the substratum before planting may increase the burrowing rates, thereby reducing the risks of seed dislocation and mortality. Additional studies are required to determine optimal substratum acclimation times and techniques.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.024
Threshold uncertainty score0.048

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.029
GPT teacher head0.317
Teacher spread0.289 · 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 source (direct Gemma or distilled Codex), 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

Citations16
Published2010
Admission routes2
Has abstractyes

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