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Record W2359404163

The Impact of The Traditional Chinese Medical Additive on the Enteric Bacterium and Productive Trait of growing Pigs

2003· article· en· W2359404163 on OpenAlexaff
Zeng Dai-qin

Bibliographic record

VenueSichuan Animal and Veterinary Sciences · 2003
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicMedicinal Plant Pharmacodynamics Research
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsCoccus (insect)Feed additiveBiologyWeaningHerbTraitFood scienceAnimal scienceBiotechnologyTraditional medicineMedicinal herbsBotanyMedicine
DOInot available

Abstract

fetched live from OpenAlex

In this study,We used the traditional chinese medical additive which was made of Eucommia-leaf,hawthorn and the root of membranous milk vetch etc to feed growing pigs in order to find the impact on enteric germs and productive trait in weaning piglets.The results showed that in the three test groups,the Lactic acid bacteria (LAB)and Bifidobacterium were higher than the control group (P0.05),while the indexes of E.col and enteric coccus and diarrhoea ratio declined obviously.Compared with the control group,the average daily gain of the test groups was raised9.2%,5.5%,and13.32%,feedstuff reward was raised9.8%,6.64%,15.03%,in which the test groupⅢwas the best (P0.05).This study indicated that the traditional chinese medical additive could not promote the beneficial bacterium of weaning piglets proliferation but also improve the productive trait,whether it was powder preparation or extractor preparation.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.183
GPT teacher head0.457
Teacher spread0.274 · 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.

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

Citations0
Published2003
Admission routes1
Has abstractyes

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