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Record W1825358797 · doi:10.3233/wor-2006-00550

Cut-points to prevent low back injury due to force exertion at work

2006· article· en· W1825358797 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

VenueWork · 2006
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsExertionWork (physics)Physical medicine and rehabilitationPerceived exertionPhysical therapyMedicineComputer scienceEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Force exertion is related to low back injuries (LBI). This paper critically reviews the literature concerning cut-points for back force exertion, presents available guidelines in a concise manner, and identifies areas that need further research. The studies reviewed were grouped according to the criteria used to set the cut-point values. Most often cut-points differ than concur. The approach considering physiological, psychophysical, epidemiological, and biomechanical aspects of back force exertion meets the most known criteria and presents the lowest common denominator of instantaneous load for lifting tasks. Further experimental and epidemiological studies in peak load and cumulative exposure are necessary. Compound indices should also be developed for pushing, pulling, and carrying. Future indices should consider electromyographically determined fatigue, differential viscoelastic properties of tissues, aging, and the cross sectional area of back muscles. We hope that this paper contributes to a more systematic appraisal of back force exertion at work.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.860
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.003

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 head0.006
GPT teacher head0.255
Teacher spread0.249 · 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