ArticleChinese herbal medicines2023
Geographical discrimination of
Article in Chinese herbal medicines, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed, 10 citations in OpenAlex.
- Exploring the global mosaic of medicinal plant databases: unveiling nature's pharmacopoeia.Natural products and bioprospecting · 2026Review
- Towards a Standardized Approach for the Geographical Traceability of Plant Foods Using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) and Principal Component Analysis (PCA).Foods (Basel, Switzerland) · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Objective: This paper focused on the geographical discrimination of Methods: In this study, eleven trace element concentrations were determined by ICP-OES and processed by multivariate statistical analysis. Results: Based on ANOVA, the mean concentrations of 10 elements except Co differed significantly among six origins. Pearson's correlation analysis showed that 11 pairs of elements have a positive significant correlation and 12 pairs have a negative significant correlation. The geographical origins were effectively differentiated using the eleven elements combined with PCA. And the S-LDA model offered a 100% differentiation rate. Conclusion: The overall results suggested that the combination of multielement analysis by ICP-OES and chemometrics multivariate could trace the geographical origins of tea. And the paper can provide reference for quality control and quality evaluation of
Indexed as
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.