Intrinsic, reflex and voluntary contributions to task-dependent joint stiffness
Bibliographic record
Abstract
Dynamic joint stiffness defines the dynamic relationship between the position of the joint and the torque acting about it. Joint stiffness consists of two components: intrinsic and reflex stiffness. Previous work from our lab has shown that subjects can alter their reflex stiffness voluntarily and independently of intrinsic stiffness. Numerous studies have investigated whether reflex stiffness is altered in a task-dependent fashion; however the results of these studies are inconclusive. We designed an experimental paradigm where subjects were faced with 3 tasks: one task where joint stiffness aided subjects, a second where joint stiffness hindered the subjects and a third where joint stiffness had no effect. We found that subjects did not alter their joint stiffness to perform the different tasks. Rather, they performed the tasks by voluntarily producing the appropriate torque based on visual feedback. Thus, with the paradigm used in this study, reflex stiffness was not modulated in a task-dependent manner.
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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 | 0.009 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".