MétaCan
Menu
Back to cohort
Record W3137149864 · doi:10.15584/ejcem.2020.4.1

Short-term comparison of the 660 and 830 nm laser in the treatment of temporomandibular dysfunction – a randomized clinical trial

2021· article· en· W3137149864 on OpenAlexaboutno aff
Camila Simon, Cássio Brendon dos Santos, Carla de Fátima Albuquerque, L. Hoffmann, Fernando Amâncio Aragão, Gladson Ricardo Flôr Bertolini

Bibliographic record

VenueEuropean Journal of Clinical and Experimental Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicLaser Applications in Dentistry and Medicine
Canadian institutionsnot available
Fundersnot available
KeywordsLow level laser therapyVisual analogue scaleMedicineRandomized controlled trialSingle blindDentistryLaser therapyMcGill Pain QuestionnairePhysical therapyInternal medicineLaser

Abstract

fetched live from OpenAlex

Introduction. The objective of this study was to compare the effects of low-level laser therapy (LLLT), 660nm laser with 830nm, in temporomandibular dysfunction (TMD). Aim. To compare the effect of LLLT 660 nm and 830 nm in treatment of TMD. Material and methods. This is a randomized clinical study, composed of 30 volunteers with TMDs selected and divided into three groups: LLLT 660nm, LLLT 830nm and Sham. After the intervention, the results were reevaluated with the Fonseca anamnestic questionnaire (FAQ), American Academy of Orofacial Pain Questionnaire (AAOPQ), McGill Pain Questionnaire and Visual Analog Scale. Results. Analysis of the results showed that, although all groups had reduced values in the FAQ, only the laser groups presented alterations in the level of classification; for AAOPQ, only the treatment groups had a reduction in the positive responses, variables, the reduction was similar for all groups. Conclusion. LLLT produced a reduction in severity of symptoms but was like the sham for pain.

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)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.011
Threshold uncertainty score0.036

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0050.003
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0030.002
Insufficient payload (model declined to judge)0.0110.001

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 head0.118
GPT teacher head0.459
Teacher spread0.340 · 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 designRandomized trial
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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueEuropean Journal of Clinical and Experimental MedicineSame topicLaser Applications in Dentistry and MedicineFrench-language works237,207