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Record W2767830899 · doi:10.1002/fsn3.548

Nutritional value of raw <i>Canavalia ensiformis</i> and its utilization as partial replacement for soybean meal in the diet of <i>Clarias gariepinus</i> (Burchell, 1822) fingerlings

2017· article· en· W2767830899 on OpenAlexfundno aff
S. G. Solomon, Victor Tosin Okomoda, Obekpa Oguche

Bibliographic record

VenueFood Science & Nutrition · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsnot available
FundersNova Scotia Department of Fisheries and Aquaculture
KeywordsCanavalia ensiformisMealSoybean mealClarias gariepinusBiologyNutrientFish mealFood scienceAnimal scienceAgronomyFish <Actinopterygii>Raw materialFisheryEcology

Abstract

fetched live from OpenAlex

Abstract The nutritional value of raw Jack bean meal (Canavalia ensiformis) as a partial substitute for soybeans meal was investigated in this study. Preliminary investigation on nutrient composition revealed that lysine, histidine, and phenylalanine were significantly higher in C. ensiformis seed meal compared to soybean meal. However, crude protein and other essential amino acids were significantly lower. Feeding trial was then conducted to investigate the effect of replacing about 40% soybeans meal (at 58.8% inclusion) with C. ensiformis in the diet of Clarias gariepinus. The result obtained after 56 days revealed that fingerlings could tolerate up to 20% replacement without significant effect on growth and nutrient utilization. Beyond this, growth was significantly reduced. Survivals of the fish also follow a similar trend as stated above. It was concluded that dietary inclusion of raw C. ensiform meal should not be beyond 11% (or 20% replacement for soybeans meal included at 58.8%) in the diet of C. gariepinus.

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 score0.004
Threshold uncertainty score0.008

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 head0.055
GPT teacher head0.289
Teacher spread0.234 · 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

Citations21
Published2017
Admission routes1
Has abstractyes

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