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Record W4313331997 · doi:10.1111/raq.12780

Mineral nutrition in penaeid shrimp

2022· article· en· W4313331997 on OpenAlexaff
Ha H. Truong, Barney M. Hines, Maurício Gustavo Coelho Emerenciano, David Blyth, Sarah E. Berry, Tansyn H. Noble, Nicholas Bourne, Nicholas M. Wade, Artur Rombenso, Cedric J. Simon

Bibliographic record

VenueReviews in Aquaculture · 2022
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsGovernment of Northwest Territories
FundersCommonwealth Scientific and Industrial Research Organisation
KeywordsShrimpPenaeus monodonPenaeidaePenaeusAquacultureFisheryBiologyCrustaceanShrimp farmingDecapodaFish <Actinopterygii>

Abstract

fetched live from OpenAlex

Abstract This review summarises the current knowledge of mineral nutrition for penaeid shrimp. It investigates how the aquatic environment and the lifecycle of shrimp affect requirements and the role that minerals play in shrimp health. Methods of supplying minerals via either water or to feed, and novel ways of supplementing minerals within feed, are discussed. The requirements for individual minerals are summarised with recommendations for minimum levels of dietary inclusion for semi‐intensive and intensive commercial shrimp culture presented where data permits. Estimates of dietary requirement remain broad for most minerals for the main shrimp production species ( Penaeus vannamei , Penaeus monodon and Penaeus japonicus ), with some essential minerals remaining unstudied (Table 2 in Section 5.10). Mineral nutrition will become more important as intensification and diversification of production systems provide new challenges to shrimp aquaculture.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.258
Teacher spread0.229 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations63
Published2022
Admission routes1
Has abstractyes

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