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Record W1850241250 · doi:10.5376/ija.2015.05.0025

Evaluation on the effect of local and imported yeast as supplementary feed on African catfish (<i>Clarias gariepinus</i> Burchell, 1822) in Egypt

2015· article· en· W1850241250 on OpenAlexvenueno aff
M. H. Mona, A. A. Alamdeen, Ensaf El-Gayar, Ahmed Heneish, El-feky Mohamed M. M.

Bibliographic record

VenueInternational Journal of Aquaculture · 2015
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsnot available
Fundersnot available
KeywordsClarias gariepinusCatfishFisheryBiologyYeastFish <Actinopterygii>Biochemistry

Abstract

fetched live from OpenAlex

This study aims to evaluate the effect of different graded levels of local and imported yeast ( Saccharomyces cerevisiae ) on growth performance of African catfish, Clarias gariepinus . A total of 250 fingerlings of the African catfish Clarias gariepnus were collected from Edku Lake for the experiment. The fish were divided into 5 groups, containing of 50 fish in each group. Describe the group and treatment given to each group of the fish. The results showed that the supplementation of local yeast, improved the growth and feed utilization. Significant results were recorded for treatment of G2 compared to the G1. It was shown that the yeast supplementation significantly affected the whole-fish body composition. All treatments exhibited higher values compared to the G1. Treatment of G2 also showed the lowest values for dray matter, ether extract and ash content, while it showed highest value for crude protein compared to the G1. Hematological analysis of all the treatments showed satisfactory values compared to the G1. From the economic point of view, the utilization of local baker's yeast for African catfish could reduce the cost, while increases the growth and production performance under farming conditions.

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 score0.004
Threshold uncertainty score0.007

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 head0.022
GPT teacher head0.268
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

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

Citations0
Published2015
Admission routes1
Has abstractyes

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