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Traditional Chinese Medicine for Managing Inflammatory Pain of Arthritis with Herbal Medicines

2016· article· en· W2572771186 on OpenAlexaff
Jieyu Zuo, Zheng Qin, Hui Jian, Tasha Porttin, Chanelle Willson, Fiona Misquita, Jordan Capicio, Raimar Löbenberg

Bibliographic record

VenueCurrent Traditional Medicine · 2016
Typearticle
Languageen
FieldMedicine
TopicNatural Compounds in Disease Treatment
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineRheumatoid arthritisAlternative medicineArthritisTraditional Chinese medicineTraditional medicineOsteoarthritisChinese herbsMedicinal herbsIntensive care medicineInternal medicinePathology

Abstract

fetched live from OpenAlex

Arthritis is an inflammatory condition that affects millions of people worldwide. However, this condition is often difficult to treat because of the extensive individual variability in disease presentation. Traditional Chinese Medicine (TCM) represents one of the first holistic approaches for managing the inflammatory pain associated with arthritis. As a major component of TCM, herbs and herbal formulas are considered to possess anti-arthritic and symptom relief properties. Compared to Western Medicine, which focuses on the use of single- ingredient pharmaceuticals, TCM often involves multi-herb therapies. Much of the evidence surrounding herbal remedies is anecdotal, and scientific research is lacking. Therefore, consumers are confronted with the risk of using unstandardized treatments. This review highlights the current science and knowledge of major herbs used in TCM to treat arthritis. Keywords: Arthritis, herbs, inflammation, osteoarthritis, pain, rheumatoid arthritis, traditional Chinese Medicine.

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)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.009
Threshold uncertainty score0.031

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0090.002

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 head0.052
GPT teacher head0.300
Teacher spread0.249 · 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 designNot applicable
Domainnot available
GenreReview

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
Published2016
Admission routes1
Has abstractyes

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