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An Examination of Shoulder Postures and Moments of Force Among Different Skill Levels in the Wool Harvesting Industry

2009· article· en· W2043765793 on OpenAlexaff
Diane E. Gregory, Poonam Pal, Allan Carman, Stephan Milosavljevic, Jack P. Callaghan

Bibliographic record

VenueInternational Journal of Occupational Safety and Ergonomics · 2009
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsWoolQuality (philosophy)Agricultural engineeringMathematicsEngineeringMaterials science

Abstract

fetched live from OpenAlex

The wool harvesting industry employs workers of varying skill levels that differ in both quality and number of harvested fleeces. As it was unknown how skill affected parameters such as joint posture and loading, the current study comparatively examined 140 wool harvesting workers representing 4 skill levels during wool harvesting competitions. Three-dimensional upper limb postures and peak and cumulative shoulder moments were calculated for each worker. Results indicated that elite wool harvesters, in general, used different shoulder postures to perform the harvesting tasks and were thus exposed to different shoulder moments as compared to the lower skill levels. It is plausible that these adopted postures allow the higher class workers to perform their job with higher quality and greater speed as compared to the lower ranked workers. Posturalbased training may help improve technique in lower ranked workers and enable these workers to achieve higher ranked status.

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)0.001
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 score0.135
Threshold uncertainty score0.220

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 communication0.0000.000
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 head0.022
GPT teacher head0.333
Teacher spread0.310 · 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

Citations10
Published2009
Admission routes1
Has abstractyes

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