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Record W3027043996

섬유근통 증후군에 대한 치험 2례

2020· article· ko· W3027043996 on OpenAlexaboutno aff
임민영, 이현종, 임성철, 이윤규

Bibliographic record

VenueKorean Journal of Acupuncture · 2020
Typearticle
Languageko
FieldMedicine
TopicHealthcare and Venom Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineFibromyalgiaAcupuncturePhysical therapyBee venomAlternative medicinePathology
DOInot available

Abstract

fetched live from OpenAlex

Objectives : The purpose of this study was to report the effects of Korean medicine therapy on patients with fibromyalgia syndrome. Methods : In this study, we used Korean medicine treatments, including acupuncture, bee venom therapy, chuna manual therapy, and others, to treat hospitalized patients diagnosed with fibromyalgia syndrome. Improvements in clinical symptoms were evaluated using a numeric rating scale (NRS), the short form McGill Pain Questionnaire (SF-MPQ), and changes in the number of tender points. Results : After Korean medicine treatment, the NRS scores reduced from 10 to 7 (Patient 1) and from 10 to 5 (Patient 2). The SF-MPQ scores decreased from 33 to 26 (Patient 1) and from 25 to 18 (Patient 2). The number of tender points reduced from 18 to 15 (Patient 1) and from 12 to 11 (Patient 2). Conclusions : In both patients, the NRS scores, SF-MPQ scores, and number of tender points significantly improved. The results suggest that Korean medicine treatments, including acupuncture, bee venom therapy, chuna manual therapy, and others, may be effective for treating fibromyalgia syndrome.

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: Case report · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.070
GPT teacher head0.361
Teacher spread0.292 · 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 designCase report
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

Citations0
Published2020
Admission routes1
Has abstractyes

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