Computation of Trunk Muscle Forces and Internal Spinal Loads in Standing Postures
Bibliographic record
Abstract
The kinetic redundancy in human musculoskeletal trunk system allows for the active control of posture during a specific task while satisfying equilibrium and stability requirements. Such control could aim, for example, to minimise forces in active musculature and stresses in passive tissues. It results in a superfluous system of equations the solution of which not yet satisfactorily achieved despite its importance in evaluation and treatment of spinal disorders. Due to shortcomings in existing reduction, optimisation and EMG-driven models, and combination thereof, a novel kinematics-based finite element approach [1,2] is employed that fully accounts for the synergy between passive and active trunk sub-systems. In this study, the kinematics-based model is applied to determine spinal muscle forces and internal ligamentous passive loads at different disc levels in standing postures under gravity loads with and without 200N weights carried in both hands (positioned symmetrically close to the body, either anteriorly or on sides).
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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".