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Record W2031729314 · doi:10.1080/00140139.2014.980336

Effects of height and load weight on shoulder muscle work during overhead lifting task

2014· article· en· W2031729314 on OpenAlex

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

VenueErgonomics · 2014
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsInstitut de recherche Robert-Sauvé en santé et en sécurité du travailUniversité de MontréalUniversité du Québec à Montréal
Fundersnot available
KeywordsIsometric exerciseRotator cuffWork (physics)ElectromyographyDeltoid curvePhysical medicine and rehabilitationMedicinePhysical therapySimulationComputer scienceEngineeringAnatomy

Abstract

fetched live from OpenAlex

Few musculoskeletal models are available to assess shoulder deeper muscle demand during overhead lifting tasks. Our objective was to implement a musculoskeletal model to assess the effect of lifting height and load on shoulder muscle work. A musculoskeletal model scaled from 15 male subjects was used to calculate shoulder muscle work during six lifting tasks. Boxes containing three different loads (6, 12 and 18 kg) were lifted by the subjects from the waist to shoulder or eye level. After optimisation of the maximal isometric force of the model's muscles, the bio-fidelity of the model was improved by 19%. The latter was able to reproduce the subjects' lifting movements. Mechanical work of the rotator cuff muscles, upper trapezius and anterior deltoid was increased with lifting load and height augmentation. In conclusion, the use of a musculoskeletal model validated by electromyography enabled to evaluate the muscle demand of deep muscles during lifting tasks.

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)0.000
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.748
Threshold uncertainty score0.388

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 head0.004
GPT teacher head0.222
Teacher spread0.218 · 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