Low back loads while walking and carrying: comparing the load carried in one hand or in both hands
Bibliographic record
Abstract
This study investigates the consequences of carrying load in one hand versus both hands. Six participants walked carrying buckets containing various weights. The weight was either carried in one hand or distributed evenly between both hands. Electromyography, force plate and body kinematic data were input to a three-dimensional anatomically detailed model of the spine to calculate spine loading. Carrying loads in one hand resulted in more load on the low back than when the load was split between both hands. When carrying 30 kg in one hand, the low back compression exceeded 2800 N; however, splitting the load between hands reduced low back compression to 1570 N (reduction of 44%). Doubling the total load by carrying 30 kg in each hand actually produced lower spine compression than when carrying 30 kg in one hand. Balancing the load between both hands when carrying material has merit and should be considered when designing work. PRACTITIONER SUMMARY: Carrying a load in one hand (30 kg) resulted in more spine load than splitting the same load between both hands (15 kg). When carrying double the load in both hands (30 kg in each hand vs. 30 kg in one hand), spine load decreased, suggesting merit in balancing load when designing work.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 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".