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Record W2985652405

Effects of local vibration therapy on various performance parameters: a narrative literature review.

2018· article· en· W2985652405 on OpenAlexaff
Darrin Germann, Amr El Bouse, Jordan Shnier, Nader Abdelkader, Mohsen Kazemi

Bibliographic record

VenuePubMed · 2018
Typearticle
Languageen
FieldMedicine
TopicEffects of Vibration on Health
Canadian institutionsCanadian Memorial Chiropractic College
Fundersnot available
KeywordsFlexibility (engineering)Computer scienceSet (abstract data type)Inclusion (mineral)Narrative reviewOutcome (game theory)VibrationDuration (music)MedicinePhysical medicine and rehabilitationPhysical therapyBioinformaticsChemistryMathematicsBiologyStatisticsIntensive care medicinePhysicsAcoustics
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTION: The therapeutic effects of local muscle vibration (LMV) remain controversial due to a lack of specific protocols. This review was conducted to better understand the effects of various LMV application protocols. METHODS: A comprehensive literature search was performed based on title and abstract and a set of predetermined inclusion criteria. Study quality was then evaluated via the PEDro scale. RESULTS: 23 articles were returned initially, and 21 studies were evaluated. The average PEDro score was 5.97/10. Reported outcome measures included muscle activation, strength, power, and range of motion / flexibility. The frequency and amplitude of LMV ranged from 5 - 300 Hz and 0.12-12 mm respectively, and duration from 6 seconds - 30 minutes. CONCLUSION: Most studies found that LMV elicits beneficial changes in the mentioned outcome measures. However, the methodological procedures used are quite heterogeneous. Further research is needed to understand the optimal application of LMV.

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)0.003
metaresearch head score (Gemma)0.009
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 score0.006
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0060.006
Science and technology studies0.0000.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.014
GPT teacher head0.280
Teacher spread0.266 · 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

Citations42
Published2018
Admission routes1
Has abstractyes

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Same venuePubMedSame topicEffects of Vibration on HealthFrench-language works237,207