The relationship between trunk muscle activation and trunk stiffness: examining a non-constant stiffness gain
Bibliographic record
Abstract
The relationship between muscle activation, force and stiffness needs to be known to interpret the stability state of the spine. To test the relationship between these variables, a quick release approach was used to match quantified torso stiffness with an EMG activation-based estimate of individual muscle stiffnesses. The relationship between activation, force and stiffness was modelled as k = q x F/l, where k, F and l are muscle stiffness, force and length, respectively, and q is the dimensionless stiffness gain relating these variables. Under the tested experimental scenario, the 'stiffness gain', q, which linked activation with stiffness, demonstrated a decreasing trend with increasing levels of torso muscle activation. This highlights the likelihood that the choice of a single q value may be over simplistic to relate force to stiffness in muscles that control the spine. This has implications for understanding the potential for spine instability in situations requiring high muscular demand.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".