Reliability of maximal static strength measurements of the arms in subjects with hemiparesis
Bibliographic record
Abstract
OBJECTIVE: To evaluate the reliability of maximal static strength measurements of five arm muscle groups and of strength ratios (paretic/non-paretic) in subjects with poststroke hemiparesis. DESIGN: The generalizability theory was used to estimate the reliability coefficients and standard errors of measurement of maximal strength for various combinations of trials and sessions and of the strength ratios for one and two sessions. Grip maximal voluntary force and/or maximal voluntary torques exerted by flexor and extensor muscles at both the elbow and shoulder joints were measured in 17 subjects with poststroke hemiparesis. Multiple trials were performed by subjects during two sessions. SETTING: Rehabilitation centre. SUBJECTS: A convenience sample of 17 subjects with poststroke hemiparesis. RESULTS: The reliability coefficients for the strength measurements were in the range of 0.81-0.97 with standard errors of measurement accounting for 4% to 20% of the group means. For the strength ratios, the coefficients of generalizability ranged from 0.76 to 0.95 with standard errors of measurement equal to 6% to 19% of the group means. CONCLUSIONS: The maximal strength measurements of the arms in subjects with hemiparesis are reliable. The strength ratios are also reliable and can be used to quantify strength impairment.
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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 | 0.005 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.001 | 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".