Does the margin of stability measure predict stability of gait with a constrained base of support?
Bibliographic record
Abstract
ABSTRACT This study aimed to determine the validity of the centre of mass position (COM) position and extrapolated COM (XCOM), relative to the base of support, for predicting stability during a walking task where the base of support is constrained. Nine young healthy participants walked on a narrow beam. Three-dimensional motion capture was used to calculate the COM and XCOM relative to the base of support. Steps were classified as having either the COM or XCOM inside or outside the base of support, and were classified as successful (stable – foot placed on the beam) or failed (unstable – foot stepped off the beam). If the COM or XCOM are valid measures of stability, they should be within the base of support for successful steps and outside the base of support for failed steps. Classifying the COM and XCOM inside or outside the base of support correctly predicted successful or failed steps in 69% and 58% of cases, respectively. When the COM or XCOM were outside the base of support, walking faster seemed to help participants to maintain stability. The further the COM or XCOM were outside the base of support during a successful step, the more likely participants were to fail on a subsequent step. The results of this study suggest that both COM and XCOM are valid measures of stability during a beam walking task, but that classifying COM and XCOM as inside or outside the base of support may be over-simplistic.
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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 | 0.002 | 0.011 |
| 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 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".