Effects of lumbar curvature on low back pain risk factors during repetitive postural loading
Bibliographic record
Abstract
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.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".