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Record W4414850346 · doi:10.1080/1091367x.2025.2567370

Measurement Properties and Muscular Demands of a Pneumatic Pain Meter: A Laboratory-Controlled Study

2025· article· en· W4414850346 on OpenAlexafffund
Allyson Summers, Ann McGrath, Mona Frey, Arnold Yu Lok Wong, Diana De Carvalho

Bibliographic record

VenueMeasurement in Physical Education and Exercise Science · 2025
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsMemorial University of Newfoundland
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsElectromyographyPhysical strengthWork (physics)Reliability (semiconductor)Biomechanics

Abstract

fetched live from OpenAlex

We determined muscular demand, within-day instrument reliability, and criterion-concurrent validity of a pneumatic pain meter device. Fifty healthy adults (22 males, 28 females; age 23 ± 6 years) completed 30 block-randomized trials meeting target levels between 10 and 100 with concurrent measures of electromyography. Experimental pain was induced over the low back and pain ratings were taken on the device as well as a 100 mm visual analog scale before induction and at 10, 20 and 30 min. Electromyography levels significantly increased from target levels 0 to 100 (p < .001), and no significant fatigue, identified as a shift in median power frequency, was identified (p = .095). Within-day reliability was excellent: ICC3,1 = 0.998 (95% confidence interval 0.997–0.998). A Bland-Altman analysis showed that 95% of the differences between the pain meter and visual analog scale fall within limits of agreement of +13.27 and −18.62. Future work should confirm measurement metrics in special populations and extended periods of time.

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 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)0.006
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.871
Threshold uncertainty score0.345

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.030
GPT teacher head0.289
Teacher spread0.259 · 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 teacher head, 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
Published2025
Admission routes2
Has abstractyes

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