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Record W2557045493 · doi:10.5376/ija.2016.06.0020

Growth Performance of Clarias gariepinus Fed Varying Levels of Sorghum bicolor Waste Meal

2016· article· en· W2557045493 on OpenAlexvenueno aff
Tiamiyu L.O., Okomoda V.T., Ogodo J.U.

Bibliographic record

VenueInternational Journal of Aquaculture · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsnot available
Fundersnot available
KeywordsClarias gariepinusSorghum bicolorSorghumMealBiologyFisheryToxicologyAgronomyFish <Actinopterygii>Food scienceCatfish

Abstract

fetched live from OpenAlex

Sorghum bicolor waste meal is a by-product of sorghum fermentation and contain about 11% crude protein, the process involve in it’s production make it an excellent unconventional feed stuff for animal nutrition, however little is known about it potential in fish nutrition. This study was therefore designed to investigating it’s nutritional value in the diet of African catfish Clarias gariepinus. Iso-nitrogenous diets were formulated with Sorghum bicolor waste meal included at 5, 10, 15 and 20%. Fingerlings (2.01g) were fed for 56 day and the growth performance and nutrient utilization determined. Result obtained shows that  Sorghum bicolor waste meal can be included up to 20% without any negative effect on growth ( P <0.05), fermentation process involved in the production of the unconventional feed stuff was largely thought to have improved the feed digestibility

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 score0.005
Threshold uncertainty score0.009

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 head0.024
GPT teacher head0.241
Teacher spread0.217 · 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

Citations7
Published2016
Admission routes1
Has abstractyes

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