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Record W2056639325 · doi:10.1155/2014/486842

Ginsenosides in Commercial Ginseng Products Analyzed by Liquid Chromatography-Tandem Mass Spectrometry

2014· article· en· W2056639325 on OpenAlexaff
Linda Uhr, Yu‐Chun Chen, Daniel Sit, Paul C. H. Li

Bibliographic record

VenueISRN Analytical Chemistry · 2014
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGinseng Biological Effects and Applications
Canadian institutionsHealth CanadaSimon Fraser University
Fundersnot available
KeywordsGinsengChromatographyGinsenosideChemistryGinsenoside Rg1Internal standardMass spectrometryLiquid chromatography–mass spectrometryTandem mass spectrometryQuality standardMedicine

Abstract

fetched live from OpenAlex

Although the LC/MS-MS method has been developed to analyze ginsenosides in ginseng roots, this method has not yet been utilized to quantify ginsenosides in ginseng products. In this paper, an internal standard method by LC/MS-MS was developed to analyze the ginsenosides content in the commercial ginseng products such as the ginseng capsules. We compare the standard addition method and the internal standard methods for the quantification of several ginsenosides (e.g., Rb1, Rb2, Rb3, Rc, Rd, Re, Rg1, and Rg3) in five commercial ginseng capsules. The results showed that the internal standard method is as good as the standard addition method and is a less tedious approach.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.000
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 head0.008
GPT teacher head0.249
Teacher spread0.240 · 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

Citations6
Published2014
Admission routes1
Has abstractyes

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