A novel approach to evaluate abdominal coactivities for optimal spinal stability and compression force in lifting
Bibliographic record
Abstract
A novel optimisation algorithm is developed to predict coactivity of abdominal muscles while accounting for both trunk stability via the lowest buckling load (P(cr)) and tissue loading via the axial compression (F(c)). A nonlinear multi-joint kinematics-driven model of the spine along with the response surface methodology are used to establish empirical expressions for P(cr) and F(c) as functions of abdominal muscle coactivities and external load magnitude during lifting in upright standing posture. A two-component objective function involving F(c) and P(cr) is defined. Due to opposite demands, abdominal coactivities that simultaneously maximise P(cr) and minimise F(c) cannot exist. Optimal solutions are thus identified while striking a compromise between requirements on trunk stability and risk of injury. The oblique muscles are found most efficient as compared with the rectus abdominus. Results indicate that higher abdominal coactivities should be avoided during heavier lifting tasks as they reduce stability margin while increasing spinal loads.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".