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Record W1120221330 · doi:10.3233/oer-2003-3102

Effects of lumbar curvature on low back pain risk factors during repetitive postural loading

2003· article· en· W1120221330 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

VenueOccupational Ergonomics · 2003
Typearticle
Languageen
FieldMedicine
TopicMusculoskeletal pain and rehabilitation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsLow back painMedicineLumbarTrunkTorsoPhysical medicine and rehabilitationLordosisBack painPhysical therapyWork (physics)Lumbar spineSurgeryAnatomyEngineeringRadiography

Abstract

fetched live from OpenAlex

Effects of lumbar spine curvature on reducing risk factors for reporting low back pain (LBP) at work were assessed for a “light” but repetitive simulated workplace assembly job. Nine women stood at a target trunk angle of 30° and assembled plastic toys on a table for 25 minutes in one minute work cycles, at a work/recovery ratio of 55/5 seconds. Flexed (rounded back) postures, often observed in industry, and lordotic (hollow back) postures maintained by back extensor muscles and proposed to reduce risk by reducing shear forces, were studied. Spinal loading was imposed by torso weight only. Twenty-five minutes of this simulated job produced discomfort scaled as “strong” to “very strong” regardless of spinal posture. Lordosis required median EMGs of 15% MVC. Flexed postures lowered back extensor EMG to as little as 5% MVC but not to zero. This apparently “light” job seems to expose people to quite high risk of reporting LBP (estimated at about 80%), mainly because of high cumulative spine loads, regardless of the spinal posture adopted.

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)0.002
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 score0.095
Threshold uncertainty score0.544

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
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 head0.006
GPT teacher head0.240
Teacher spread0.235 · 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