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Record W3041306629 · doi:10.5376/mpr.2020.10.0002

Chinese Patent Traditional Medication Containing Aristolochic Acid and its Herbal Medicinal Plant, Efficacy and Harmfulness

2020· article· en· W3041306629 on OpenAlexvenueno aff
Xuanjun Fang

Bibliographic record

VenueMedicinal Plant Research · 2020
Typearticle
Languageen
FieldMedicine
TopicNephrotoxicity and Medicinal Plants
Canadian institutionsnot available
Fundersnot available
KeywordsAristolochic acidAristolochiaceaeAristolochiaTraditional medicineMedicineMedicinal plantsBiologyBotany

Abstract

fetched live from OpenAlex

The nephrotoxicity of traditional herbal medications containing aristolochial acid has attracted wide attention in China and abroad, and some countries have banned the use of traditional herbal medications containing aristolochic acid. In this study, the traditional herbal materials and patent traditional herbal medications containing aristolochic acid were statistically analyzed. Among the common traditional herbal medications containing aristolochic acid, there are 14 kinds of aristolochic plants and 10 kinds of Asarum plants,of which there are 24 kinds of herbal materials from the family of Aristolochiaceae that may contain aristolochic acid and 47 kinds of patent traditional herbal medications that have been listed that may contain aristolochic acid from the genus of Aristolochia L.. In this review, these medicinal plants were systematically analyzed. It was concluded that the renal toxicity of herbal medication containing aristolochic acid should be paid enough attentions even though Aristolochia herbs have a special significance in traditional herbal medication of China.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.221
GPT teacher head0.367
Teacher spread0.146 · 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 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

Citations1
Published2020
Admission routes1
Has abstractyes

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