Comparison of Methods for Determining Parameters Related to Ankle Joint Quasi-Stiffness During Quiet Standing
Bibliographic record
Abstract
Ankle joint quasi-stiffness is a measure representing the control of quiet standing. Here we investigated three methods for determining parameters associated with ankle joint quasi-stiffness. Eleven healthy, young males were asked to stand quietly with eyes open (EO) and eyes closed (EC). Ankle joint quasi-stiffness was computed using two methods, one proposed by Winter et al. (Winter DA, et al. J Neurophysiol 80: 1211-1221, 1998) ([Formula: see text]) and another by Loram and Lakie (Loram ID, et al. J Physiol 540: 1111-1124, 2002) ([Formula: see text]). Both values were normalized using participants' body sizes. The short-term scaling exponent in stabilogram diffusion analysis ([Formula: see text]), which has been linked to quasi-stiffness, was applied. A two-way repeated measures ANOVA revealed a significant main effect of methodology (p < 0.0001, partial η² = 0.42), but no significant effect of eye condition (p = 0.1947, partial η² = 0.06), nor interaction effect (p = 0.4742, partial η² = 0.02). Intraclass Correlation Coefficient (ICC(3,1)) analysis indicates good reliability between [Formula: see text] and [Formula: see text] with an ICC value of 0.858 (p < 0.001) in the EO condition, and moderate reliability with an ICC value of 0.718 (p = 0.004) in the EC condition. [Formula: see text] and [Formula: see text] exhibited a very strong negative correlation in the EO ([Formula: see text] = -0.909) condition and a moderately strong negative correlation in the EC ([Formula: see text] = -0.782) condition. [Formula: see text] and [Formula: see text] exhibited moderately strong negative correlation in both the EO ([Formula: see text] = -0.664) and EC ([Formula: see text] = -0.555) conditions. The good and moderate reliability between [Formula: see text] and [Formula: see text] suggests that both measures capture similar stiffness attributes relating to their neuro-mechanical components, despite a significant methodological difference. Additionally, relatively high correlations of [Formula: see text] with [Formula: see text] and with [Formula: see text] suggest that the stochastic characteristics of centre of pressure in the short period indeed reflect the overall quasi-stiffness at the ankle joint.
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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 | 0.007 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".