MétaCan
Menu
Back to cohort
Record W211908447 · doi:10.3233/wor-2008-00755

Perception of shoulder muscular effort during low-demand load transfer tasks

2008· article· en· W211908447 on OpenAlexaff
Rebecca L. Brookham, Jesse Moreton, Clark R. Dickerson

Bibliographic record

VenueWork · 2008
Typearticle
Languageen
FieldMedicine
TopicSports Performance and Training
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsExertionPerceptionTask (project management)Physical medicine and rehabilitationPerceived exertionPhysical strengthPhysical therapyPsychologySimulationMedicineComputer scienceEngineering

Abstract

fetched live from OpenAlex

This study focused on quantifying the mathematical relationship between shoulder physical loading and muscular effort perception during low physical demand tasks. Subjects underwent training to calibrate to their range of shoulder strength capability. Subjects transferred visually identical bottles representing specified percentages of extended arm maximal voluntary force (MVF) in defined azimuth directions to identified targets. They then reported their percentage of perceived shoulder exertion relative to their calibrated range. Measures of physical shoulder loading were calculated from experimental data with a dynamic shoulder moment model. Shoulder reported perceived muscular exertion (RPE) values were most significantly correlated with percent MVF (r = 0.81), suggesting subjects were influenced more by the manipulated hand load than the shoulder-specific physical load. Multiple regression analyses demonstrated that other personal and task factors influenced shoulder RPE. Generally, subjects overestimated shoulder physical loading, and the quality of their perception degraded as the load increased.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.009
Threshold uncertainty score0.529

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.016
GPT teacher head0.250
Teacher spread0.234 · 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

Citations6
Published2008
Admission routes1
Has abstractyes

Explore more

Same venueWorkSame topicSports Performance and TrainingFrench-language works237,207