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Record W2566399991

Dietary ‘G-Pro’ Supplementation Effects on Growth, Carcass Composition and Digestive Enzymes in Common Carp, Cyprinus carpio (Linnaeus, 1758)

2016· article· en· W2566399991 on OpenAlexvenueno aff
B. KUMAR, P. Keshavanath

Bibliographic record

VenueInternational Journal of Aquaculture · 2016
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAquaculture Nutrition and Growth
Canadian institutionsnot available
Fundersnot available
KeywordsCyprinusCarpCommon carpBiologyFeed conversion ratioComposition (language)Animal scienceDigestive enzymeBody weightFood scienceFish <Actinopterygii>FisheryEnzymeBiochemistryEndocrinologyAmylase
DOInot available

Abstract

fetched live from OpenAlex

The effect of a commercial feed additive ‘G-Pro’ was evaluated on growth, body composition and digestive enzyme activity of common carp, Cyprinus carpio . Fry of average weight 0.8±0.03 g stocked in 25 m 3 outdoor cement tanks were fed daily on five isonitrogenous and isocaloric diets containing 0, 1, 2, 3 and 4 g G-Pro/kg diet respectively in triplicate for 140 days at 5% body weight in two equal meals. Fish fed on the feed additive incorporated diets showed improved growth performance, feed utilization and body composition compared to those fed the control diet. Growth, survival, food conversion, VSI, RNA: DNA ratio, carcass protein and fat were the best in fish fed 2 g G-Pro/kg diet. The water quality parameters monitored were within acceptable limits for carp culture. Results of this trial indicate that G-Pro exerts positive effect on the performance of common carp.

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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
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 head0.013
GPT teacher head0.260
Teacher spread0.247 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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