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Record W3099237840 · doi:10.1139/cjas-2020-0126

Evaluation of a novel hybrid 6-phytase using an updated phosphorus deficiency model in broiler chickens

2020· article· en· W3099237840 on OpenAlexvenueno aff
Tingting Wang, J. A. Jendza, Peter Ader, O. Adeola

Bibliographic record

VenueCanadian Journal of Animal Science · 2020
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAnimal Nutrition and Physiology
Canadian institutionsnot available
Fundersnot available
KeywordsPhytaseBroilerMonocalcium phosphateAnimal sciencePhosphorusBiologyHatchingFeed conversion ratioPhosphorus deficiencyBody weightChemistryEndocrinologyFish mealFish <Actinopterygii>

Abstract

fetched live from OpenAlex

One-day-old broiler chicks were used to investigate the optimal age to start feeding phosphorus (P)-deficient (PD) diets with two non-phytate P (nPP) concentrations in experiment 1, and 7-d-old broiler chicks were used to determine P equivalency of a hybrid 6-phytase to inorganic P in monocalcium phosphate (MCP) in experiment 2. In experiment 1, six treatments were prepared with 5, 6, or 7-d-old birds to start feeding PD diets with 1.3 or 1.5 g·kg−1 nPP. Age of birds to start feeding P-deficient diets tended to decrease (P = 0.052) mortality of birds during 14 d of feeding P-deficient diets. In experiment 2, twelve treatments including one basal diet, five diets supplied with 0.5, 0.9, 1.3, 1.7, or 2.1 g·kg−1 inorganic P, and six diets supplied with 250, 500, 750, 1000, 1500, or 2000 FTU·kg−1 phytase were fed to chickens from days 7 to 21 post hatching. Increasing phytase activity quadratically increased (P < 0.01) body weight gain, feed intake, and tibia ash of birds and apparent ileal digestibility and total tract retention of P. In conclusion, age of birds to start feeding PD diet affected their performance, and hybrid 6-phytase may partly replace MCP in a PD diet for broiler chickens.

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 score0.004

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)0.0000.000

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 head0.126
GPT teacher head0.290
Teacher spread0.163 · 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

Citations2
Published2020
Admission routes1
Has abstractyes

Explore more

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