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Record W2130037612 · doi:10.5539/sar.v1n2p15

Lower Dietary Inclusion of Alphamune G May Improve Performance, Hematology, Serum Biochemistry and Histology of Broiler Chicken

2012· article· en· W2130037612 on OpenAlexvenueno aff
S. A. Bolu, Kazeem Dauda Adeyemi, F. E. Sola-Ojo, A. A. Fabiyi, Adeoye T. Adedeji, O. Oluyemi, A. B. Babalola

Bibliographic record

VenueSustainable Agriculture Research · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsBroilerFeed conversion ratioWeight gainAnimal scienceCompletely randomized designUric acidSignificant differenceBiologyHematologyBody weightInternal medicineEndocrinologyMedicineImmunology

Abstract

fetched live from OpenAlex

<p>A 56-day trial was conducted on 140 day-old broiler chicks fed graded levels of Alphamune G (0.00, 0.02, 0.03, 0.04, 0.05 and 0.06%) in a completely randomized design. Feed intake and weight gain were significantly influenced (P<0.05) by the inclusion levels of Alphamune G. Bird fed 0.00% and 0.02% Alphamune had the highest and lowest feed intake, respectively. There was no significant difference in the feed intake, weight gain and feed to gain ratio of broiler birds fed 0.04 and 0.05% Alphamune G. Birds fed Alphamune at 0.04 and 0.05% had the best feed to gain ratio. Broiler chicks fed 0.04% of Alphamune G had the highest fibre, fat and ash retention (68.70, 77.46, and 59.88%, respectively). There was no significant difference (P>0.05) in the carcass characteristics of birds fed different graded levels of Alphamune G. Haematological parameters show no significant difference among levels of Alphamune G. Serum biochemical values did not show any significant effect except for cholesterol, creatinine and uric acid. Alphamune G at 0.04% inclusion in diets may help improve performance of broiler chicken.</p>

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.646
Threshold uncertainty score0.315

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.020
GPT teacher head0.279
Teacher spread0.259 · 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 teacher head, 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

Citations4
Published2012
Admission routes1
Has abstractyes

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