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Record W2147778563 · doi:10.5539/gjhs.v1n2p119

Effects of Polysaccharide Extracted from Traditional Chinese Medical Herbs on Lymphocyte Transformation Rate and AI-HI Antibody Titer in Chicks

2009· article· en· W2147778563 on OpenAlexvenueno aff
Xingyan Li, Xinli Gu

Bibliographic record

VenueGlobal Journal of Health Science · 2009
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicMedicinal Plant Pharmacodynamics Research
Canadian institutionsnot available
Fundersnot available
KeywordsPolysaccharideTraditional medicineHerbTiterAntibody titerChinese herbsImmunityTraditional Chinese medicineMedicinal herbsAntibodyAngelica sinensisImmune systemBiologyMedicineImmunologyBiochemistryPathology

Abstract

fetched live from OpenAlex

[Object]: Detect whether different concentrations of Chinese herbs compound polysaccharides (CPS), astragaluspolysaccharides (APS) and angeulica polysaccharides (ASP), epimedium herb polysaccharides (EPS) have effects onthe immunity function of healthy Roman chicken. [Method]: 260 one-day-old chickens were divided into thirteengroups randomly, 20 birds each group. The physiological saline, Chinese herbs compound polysaccharides, APS, ASPor EPS had been hypodermically injected for seven days continuously, and the blood was drawn on the 7th, 14th, 21st,28th, 35th, 42nd, 49th and 56th day to evaluate the activity of the translation rate of blood lymphocyte and AI-HI antibodytiters in chickens. [Result]: The results of the experiment showed that the translation rate of blood lymphocyte andAI-HI antibody titers increased markedly after the use of Chinese herbs compound polysaccharides, APS, ASP and EPSto the chickens. Chinese herbs compound polysaccharides had more effective function improving the translation rate ofblood lymphocyte and AI-HI antibody titers than others. [Conclusion]: The Chinese herbs compound polysaccharides,APS, ASP and EPS could promote the immunity function of the chickens. The Chinese herbs compoundpolysaccharides were the strangest one among them.

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)0.005
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.837
Threshold uncertainty score0.490

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.054
GPT teacher head0.484
Teacher spread0.430 · 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 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
Published2009
Admission routes1
Has abstractyes

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