Reducing lumbar spine loading in Russian bar porters: a case study
Bibliographic record
Abstract
The Russian bar is an acrobatic circus discipline characterised by dynamic loading on a single shoulder, posing a risk for back injuries. The aim of this case study was to quantify and compare lumbar spine loads in porters using a novel symmetrical design and the traditional asymmetrical bar. Two male porters and one female flyer performed a series of candle jumps, saltos, and consecutive jumps using both bar designs. Motion capture, electromyography, and musculoskeletal modelling in OpenSim were used to quantify L4-L5 intervertebral forces and moments. Statistical comparisons were conducted using a multifactorial analysis of variance (ANOVA). The results showed that the symmetrical bar significantly reduced lumbar spine bending moments (2.1 times lower) and shear forces (2.2 times lower) compared to the traditional bar, with no significant differences in shoulder forces. Shoulder forces did not differ significantly between bar types, suggesting that the flyer's performance, particularly jump height, was not substantially affected by the change in bar design. This novel symmetric bar design may enhance the safety and carrier of Russian bar porters. Future research should investigate the long-term effects of this design and its impact on performance adaptation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".