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Record W2096514749 · doi:10.5539/sar.v1n1p147

Response of Broilers to Graded Levels of Distillers Dried Grain

2012· article· en· W2096514749 on OpenAlexvenueno aff
S. A. Bolu, O.I. Alli, P. O. Esuola

Bibliographic record

VenueSustainable Agriculture Research · 2012
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsWeight gainBroilerStarterBody weightNutrientAnimal scienceBiologyFeed conversion ratioFood scienceEcologyEndocrinology

Abstract

fetched live from OpenAlex

A total of one hundred (100) day old broilers of mixed sexes were used to investigate the effects of graded levels of distillers dried grain on performance, nutrient utilization, and carcass evaluation. The birds were randomly allocated to five treatment groups of 20birds, and were further replicated five times. The five treatments comprised of graded levels of Distiller Dried Grain (DDG) in 0, 10, 20, 30 40% inclusion to replace maize. Feed intake, weight gain and feed/gain ratio were significantly affected (P<0.05) by levels of DDG. Average daily feed intake increased with increasing levels of DDG. Birds fed 40% DDG had the highest (72.90g/bird/day) feed intake while the birds on the control diet had the lowest (68.04g/bird/day) feed intake. Weight gain was significantly affected (P<0.05) by dietary DDG. Birds fed 10% DDG had the highest weight gain (27.95g/bird/day). Beyond this dietary inclusion level (10%), weight gain continued to decrease. Birds fed 40% DDG had the lowest weight gain (23.10g/bird/day). Nutrient retention was significantly affected (P<0.05) by dietary DDG. Protein and fat retention decreased with increase in level of dietary DDG. These nutrients were retained more by broilers fed 10% dietary level of DDG. Dietary levels of DDG had no significant influence (P<0.05) on the relative weight of the different body parts. It was concluded that up to 10% DDG can be used in broiler starter and finisher diet.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.900
Threshold uncertainty score0.444

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.069
GPT teacher head0.334
Teacher spread0.264 · 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

Citations8
Published2012
Admission routes1
Has abstractyes

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