Clinical evaluation of the refined clothespin relocation test
Bibliographic record
Abstract
BACKGROUND: The refined clothespin relocation test is a test used to evaluate the performance of a prosthesis user by analysing the compensatory motions and time to complete a grasping and placement exercise. The test has been studied previously with a motion capture laboratory and has now been adapted for a clinical setting. A comparison of prosthesis user to an able-bodied group is needed to determine efficacy as an assessment tool. OBJECTIVE: To modify the previous refined clothespin relocation test and assess whether it can distinguish between able-bodied and prosthesis users. STUDY DESIGN: Comparative analysis. METHODS: Forty-two able-bodied subjects and three prosthesis users completed the adapted refined clothespin relocation test protocol. Average refined clothespin relocation test scores describing the degree of compensatory movements and the time to complete the protocol were compared using a Mann-Whitney U-test. RESULTS: = 0.43). CONCLUSION: Prosthesis users demonstrated larger compensations and longer completion times, as reflected in the refined clothespin relocation test final score. The refined clothespin relocation test has the potential to be a useful clinical tool to assess user performance on a functional task. CLINICAL RELEVANCE: This preliminary study demonstrates that the adapted protocol can distinguish between the two groups based on refined clothespin relocation test score. A future multi-centre study is required using multiple raters and comparing it with the existing outcome measures to validate the refined clothespin relocation test and determine inter-rater reliability.
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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 | 0.008 |
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".