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Record W2323293200 · doi:10.1080/10803548.2016.1153223

A dental stool with chest support reduces lower back muscle activation

2016· article· en· W2323293200 on OpenAlex
Viet Cuong Tran, Reid Turner, Andrew MacFadden, Stephen M. Cornish, Dale Esliger, K. Komiyama, Philip D. Chilibeck

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

VenueInternational Journal of Occupational Safety and Ergonomics · 2016
Typearticle
Languageen
FieldHealth Professions
TopicOccupational health in dentistry
Canadian institutionsUniversity of ManitobaUniversity of Saskatchewan
Fundersnot available
KeywordsSittingMedicineSternumElectromyographyMuscle fatiguePhysical therapyPhysical medicine and rehabilitationSurgeryPathology

Abstract

fetched live from OpenAlex

Activation of back musculature during work tasks leads to fatigue and potential injury. This is especially prevalent in dentists who perform much of their work from a seated position. We examined the use of an ergonomic dental stool with mid-sternum chest support for reducing lower back muscle activation. Electromyography of lower back extensors was assessed from 30 dental students for 20 s during three conditions in random order: (a) sitting upright at 90° of hip flexion on a standard stool, (b) leaning forward at 80° of hip flexion on a standard stool, and (c) leaning forward at 80° of hip flexion while sitting on an ergonomic stool. Muscular activity of the back extensors was reduced when using the ergonomic stool compared to the standard stool, by 33-50% (p < 0.01). This suggests a potential musculoskeletal benefit with use of a dental stool with mid-sternum chest support.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.188
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
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 head0.400
Teacher spread0.348 · 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