Effects of height and load weight on shoulder muscle work during overhead lifting task
Bibliographic record
Abstract
Few musculoskeletal models are available to assess shoulder deeper muscle demand during overhead lifting tasks. Our objective was to implement a musculoskeletal model to assess the effect of lifting height and load on shoulder muscle work. A musculoskeletal model scaled from 15 male subjects was used to calculate shoulder muscle work during six lifting tasks. Boxes containing three different loads (6, 12 and 18 kg) were lifted by the subjects from the waist to shoulder or eye level. After optimisation of the maximal isometric force of the model's muscles, the bio-fidelity of the model was improved by 19%. The latter was able to reproduce the subjects' lifting movements. Mechanical work of the rotator cuff muscles, upper trapezius and anterior deltoid was increased with lifting load and height augmentation. In conclusion, the use of a musculoskeletal model validated by electromyography enabled to evaluate the muscle demand of deep muscles during lifting tasks.
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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) | 0.000 | 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".