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Evaluation of Low Back Pain Risks in a Beef Skinning Operation

2000· article· en· W1480563505 on OpenAlexaff
Biman Das, Arijit K. Sengupta

Bibliographic record

VenueInternational Journal of Occupational Safety and Ergonomics · 2000
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgriculture and Farm Safety
Canadian institutionsDalhousie University
Fundersnot available
KeywordsBack painLow back painBack injuryBent molecular geometrySagittal planeBack musclesPhysical medicine and rehabilitationPhysical therapyMedicineStructural engineeringEngineeringAnatomy

Abstract

fetched live from OpenAlex

The low back pain risks in a beef skinning operation at a high stand kill floor workstation was evaluated. The increases in compressive forces at lower back (L5/S1) between normal slump (back angle 25 degrees, measured in the sagittal plane) and severe (45 degrees ) and between normal slump and very severe (70 degrees ) bent back postures were 387 N or 28% and 616 N or 45%, respectively. The high spine load coupled with high level of repetition can have a high probability of fatigue failure in the spine structural members. Non-neutral back posture for a large portion of the total work time can be a low back pain risk factor. The videotape analysis showed that the times involved during the task performance for the bent back (more than 25 degrees ) and severe bent back (more than 45 degrees ) were 48.4 and 33.5% of the total cycle time, respectively. The upper limit from OWAS (Ovako Working Posture Analysis System) for bent back posture is 30% of the total cycle time. The bent and twisted back posture (both more than 25 degrees ) time was 10.4% compared to OWAS limit of 5%. This indicated that actions are needed in the near future to alleviate the risk of low back pain. Ergonomics redesign of the workstation was recommended for the operation.

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)0.002
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 score0.951
Threshold uncertainty score0.957

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0010.000

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 head0.046
GPT teacher head0.301
Teacher spread0.255 · 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

Citations4
Published2000
Admission routes1
Has abstractyes

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