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Effects of temperature, density and early weaning on the survival and growth of Atlantic ditch shrimp<i>Palaemonetes varians</i>larvae

2009· article· en· W2009169646 on OpenAlexafffund
Jorge Palma, Dominique Bureau, Miguel Correia, José Pedro Andrade

Bibliographic record

VenueAquaculture Research · 2009
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsUniversity of Guelph
FundersUniversity of Guelph
KeywordsBiologyLarvaShrimpAnimal scienceWeaningSurvival rateLive foodFisheryAquacultureEcologyFish <Actinopterygii>Internal medicine

Abstract

fetched live from OpenAlex

This investigation examined the effects of temperature, density and early weaning on the survival and growth of Palaemonetes varians larvae. Survival of larvae raised at 17.5 °C was not significantly different (average + standard deviation) (94 ± 5%) from the survival of those raised at 19.5 °C (95 ± 5%) and at 21.5 °C (94 ± 4%). However, the duration of the larval stage was significantly longer for shrimp reared at 17.5 °C (17.3 ± 0.8 days) compared with shrimp reared at 19.5 °C (14.3 ± 0.7 days) and at 21.5 °C (11.3 ± 0.6 days). No significant differences (P>0.05) were found in the survival rate, final weight and length of larvae reared at the densities of 5, 10, 20 and 50 larvae L−1. The survival of P. varians larvae fed solely on Artemia was significantly higher (P<0.05) than larvae weaned with an artificial practical diet from Zoea II stage (94 ± 4% and 82 ± 1%, respectively, for Artemia and artificial diet-fed larvae), but no significant differences (P>0.05) were observed in the final larval weight or length between these two treatments. The survival and growth of the larvae fed with the practical diet tested is a promising step ahead in the development of the culture of this species as it eliminates both the need for Artemia throughout all larval stages, and the need for more expensive artificial diets.

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)0.001
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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.824
Threshold uncertainty score0.279

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.025
GPT teacher head0.260
Teacher spread0.236 · 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 designBench or experimental
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

Citations11
Published2009
Admission routes2
Has abstractyes

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