MétaCan
Menu
Back to cohort
Record W898933308 · doi:10.1089/zeb.2014.1008

Growth, Oxygen Consumption, and Behavioral Responses of <i>Danio rerio</i> to Variation in Dietary Protein and Lipid Levels

2015· article· en· W898933308 on OpenAlexaff
Timothy M. O'Brine, Jana Vrtělová, Donna Snellgrove, Simon J. Davies, Katherine A. Sloman

Bibliographic record

VenueZebrafish · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsDanioZebrafishBiologyFood scienceFish <Actinopterygii>BiochemistryFishery

Abstract

fetched live from OpenAlex

In recent years, there has been increasing interest in the welfare of ornamental fish. Diet can significantly impact the welfare of fish, which can manifest as changes in the fish's physical health and behavior. The zebrafish, Danio rerio, is a popular ornamental species; however, little is known about their nutritional requirements with possible implications for their welfare. Here, we investigated the effect of diets with increasing crude protein (iso-caloric diets) and lipid (iso-nitrogenous diets) on the growth performance, oxygen consumption, and behavior of zebrafish. We found no significant effects of crude protein (32%-75%) or lipid (8%-16%) on the specific growth rate or oxygen consumption of fish fed 5% of their body mass (BM)/day, although the highest crude protein and lipid diet resulted in an increase in condition factor. Furthermore, the crude protein diets did not affect zebrafish behavior when fed a 2% BM ration, once a day. This study has shown that a diet with 32% crude protein and a diet with 8% crude lipid, when fed at a 5% BM ration, were sufficient to meet the growth requirements of our zebrafish. These diets supported the fish's physical health and thus benefited their welfare.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.015

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 integrity0.0000.001
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 head0.066
GPT teacher head0.270
Teacher spread0.203 · 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 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

Citations25
Published2015
Admission routes1
Has abstractyes

Explore more

Same venueZebrafishSame topicAquaculture Nutrition and GrowthFrench-language works237,207