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Record W1970221321 · doi:10.1080/00140130410001658691

Changes in physical capacity as a function of age in heavy manual work

2004· article· en· W1970221321 on OpenAlexaff
Brent Gall, W. S. Parkhouse

Bibliographic record

VenueErgonomics · 2004
Typearticle
Languageen
FieldEngineering
TopicMuscle activation and electromyography studies
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsAerobic capacityTest (biology)Work (physics)Task (project management)Physical fitnessPsychologyPhysical medicine and rehabilitationPhysical therapyMedicineEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

The objective of this study was to assess the changes in the physical capacity as a function of age in power line technicians (PLTs). The physical test was designed to closely represent the essential physical tasks of the occupation that were identified through a detailed job demand analysis. The results from the physical test showed that six out of nine test variables did not demonstrate a statistical difference between the mean scores of young (< or = 39 years) and old age (50+ years) groups. However the older group scored significantly lower in the aerobic capacity test, one-handed pull down, and both right and left standard handgrip tests. Despite these differences the older PLT appears to meet and exceed the physical requirements necessary to carry out the essential tasks of this trade. However a physical test with a high level of content and construct validity is necessary to accurately evaluate the workers physical capacity in relation to the job demands. Based on the principal of specificity for muscle training and testing, this study has demonstrated that heavy manual work appears to maintain physical capacity specific to the task as age progresses.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.013
GPT teacher head0.212
Teacher spread0.199 · 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 source (direct Gemma or distilled Codex), 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

Citations64
Published2004
Admission routes1
Has abstractyes

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