Predicting levels of basic functional mobility, as assessed by the Timed “Up and Go” test, for individuals with stroke: discriminant analyses
Bibliographic record
Abstract
PURPOSE: To compare stroke subjects with different levels of functional mobility, as determined by the Timed "Up and Go" (TUG) test, with controls and outline which clinical functional measures could be combined to predict functional mobility. METHOD: Twenty-two chronic stroke (54.7 ± 15.4 years) and 22 healthy subjects (54.7 ± 15.4 years) performed the TUG and were assessed regarding the paretic or non-dominant quadriceps strength, maximal gait speed, and quality of life (QL). Each group was divided into fast, intermediate, and slow sub-groups regarding their TUG performances. ANOVAs were employed to investigate the main and interaction effects between the groups and sub-groups and discriminant analyses to predict group membership. RESULTS: For both groups, the three sub-groups were significantly different regarding their TUG scores (26.21 < F < 32.73; p < 0.006). The significant interactions indicated that faster stroke subjects demonstrated similar TUG scores, compared to those of all the healthy sub-groups. Maximal gait speed and QL showed significant discriminant functions and correctly classified 86.4% of the original grouped cases. CONCLUSIONS: Fast stroke subjects demonstrated similar TUG performances compared to those of healthy subjects. Group membership was correctly classified for the majority of subjects, except for the fast stroke sub-group, but only for the variables related to gait speed and QL.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".