Context dependence of intrinsic and reflex contributions to ankle stiffness
Bibliographic record
Abstract
Overall joint stiffness arises from two components: intrinsic stiffness due to the mechanical properties of the joint, passive tissue, and active muscle fibers; and reflex stiffness arising from changes in muscle activation due to sensory response to stretch. This paper reviews work from my laboratory in which both empirical and system identification methods were used to assess the magnitude of intrinsic and reflex contributions to overall joint stiffness. Overall joint stiffness and the relative contributions of intrinsic and reflex mechanisms are shown to be strongly context dependent. Under stationary conditions, the perturbation properties, mean joint position and level of tonic activation have a strong effect on stiffness and its components. Changes under time-varying conditions are also substantial but differ from what stationary studies would predict. Finally, recent results are presented that indicate the CNS is capable of adjusting reflex stiffness in a task-dependent manner, even when all other variables are controlled. These results indicate that reflex contributions to joint stiffness are by no means fixed. Rather, they vary strongly with the task being performed and the context under which they are examined.
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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 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".