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Record W106983150

Effect of the Electro-acupuncture Stimulation into the Multifidus on Subjective Pain and Lumbar Flexibility in Patients with Chronic Low Back Pain

2008· article· en· W106983150 on OpenAlexaboutno aff
Wonseok Jang, Hung-Ki Park, Keunjoo Kim

Bibliographic record

VenueJournal of the Korean Society of Physical Medicine · 2008
Typearticle
Languageen
FieldMedicine
TopicHealthcare and Venom Research
Canadian institutionsnot available
Fundersnot available
KeywordsAcupunctureMedicineTrunkPhysical therapyLumbarLow back painMcGill Pain QuestionnaireFlexibility (engineering)Physical medicine and rehabilitationBack painMultifidus muscleStimulationVisual analogue scaleSurgeryInternal medicineAlternative medicine
DOInot available

Abstract

fetched live from OpenAlex

Purpose : The purpose of this study is to examine the effect of the electro-acupuncture stimulation into the multifidus for the lumbar flexibility improvement and pain reduction. The subjects were consisted of 20 women patients with chronic low back pain. Methods : 20 women patients with chronic low back pain voluntary participated for the research. 15 minute electro-acupuncture stimulation(frequency: 4Hz, Intensity: below threshold of pain) with Infra-red therapy, 3 times a week during 6 weeks period. Acupuncture application given to the patients' trigger point of the multifidus. The Application of multifidus was L3, L4, L5 spinal vertebra levels Short form McGill pain questionnaire (SFMPQ) was used to measure patient's pain level. Lumbar flexibility measurement was trunk flexion and trunk extension. Global Perceived Effect Scale(GPES) was used to measure recovery or worse of patient's condition. Results : SFMPQ was after treatment showed significantly decreased more than before stimulation treatment (P

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.006

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)0.0020.000

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 head0.013
GPT teacher head0.313
Teacher spread0.300 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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