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Record W2972799872 · doi:10.3920/978-90-8686-891-9_148

Effect of dietary amino acid to energy ratio on performance and energy utilization of broiler chickens fed high density diets

2019· article· en· W2972799872 on OpenAlexaff
Hsuan Chen, Lieske van Eck, D.M. Lamot, S. Powell

Bibliographic record

VenueEnergy and protein metabolism and nutrition · 2019
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsCargill (Canada)
Fundersnot available
KeywordsBroilerEnergy densityEnergy (signal processing)Food scienceAnimal scienceChemistryBiologyMathematicsPhysicsEngineering physicsStatistics

Abstract

fetched live from OpenAlex

The current study evaluated the effect of various amino acid (AA) to energy ratio on growth performance, carcass composition and energy utilisation of broiler chickens fed diets at three energy levels during the grower phase. Broiler chickens received common diets from 0 to 14 days. From day 14 onwards, broiler chickens were fed the experimental diets. An interaction between dietary energy and AA levels was observed on gain to feed ratio and metabolic energy efficiency. Broiler chickens fed the higher energy diet showed a higher response to dietary AA level than those fed the low energy diet. Breast meat yield linearly increased whereas fat pad yield linearly decreased in response to dietary AA level. A quadratic response of dietary energy level on fat pad yield was found. In conclusion, dietary AA content should be increased when feeding high energy diets to broiler chickens to achieve a better performance and carcass composition.

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 score0.002
Threshold uncertainty score0.003

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 head0.009
GPT teacher head0.200
Teacher spread0.191 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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