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

2016· article· en· W2572771186 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

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.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0000.000
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 head0.052
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