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Record W2380672442

Effects of Different Sources of Brown Rice Supplemented by Exogenous Enzymes of Weanling Pigs

2005· article· en· W2380672442 on OpenAlexaff
Mingzhe Fan

Bibliographic record

VenueJOURNAL OF HUNAN AGRICULTURAL UNIVERSITY · 2005
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicPhytase and its Applications
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsWeanlingPhosphorusFecesLatin squarePhytaseAnimal scienceBrown riceBiologyChemistryFood scienceRumenEndocrinologyFermentationEcology
DOInot available

Abstract

fetched live from OpenAlex

To investigate the effects of different sources of brown rice supplemented by exogenous enzymes on digestibility of phosphorus of weanling pigs,six healthy barrows,average initial body weight of (12.5±0.60) kg,were fitted with a T-cannula and fed fresh and stored brown rice according to a 6 × 6 Latin square design.There were altogether six kinds of brown rice based diets with one supplemented by exogenous emzyme combination 1,one supplemented by exogenous emzyme combination 2 and the others not supplemented by any exogenous emzyme,respectively.The result suggests that sources of brown rice,different sources of brown rice supplemented by exogenous enzymes and exogenous emzyme combinations have no effect on apparent and true ileal and fecal phosphorus digestibility values and phytate phosphorus degradability values in weanling pigs.The true ileal and fecal phosphorus digestibility values are 13.90% and 12.41% higher than the apparent ileal and fecal phosphorus digestibility values,respectively.There were no differences in true P digestibility values between the ileal and the fecal levels.The ileal phytate phosphorus degradability values are significantly lower than the fecal phytate phosphorus values.The large intestine does not play a major role in the absorption of exogenous phosphorus.

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)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score0.162

Codex and Gemma teacher scores by category

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 integrity0.0000.000
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 head0.005
GPT teacher head0.167
Teacher spread0.162 · 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

Citations0
Published2005
Admission routes1
Has abstractyes

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