Fully-automated test of upper-extremity function
Bibliographic record
Abstract
With the advent of new approaches to upper extremity recovery after stroke and spinal cord injury, the quantitative evaluation of hand function has become a crucial component of outcome evaluation. Recently we developed a workstation, the ReJoyce (Rehabilitation Joystick for Computer Exercise) on which subjects perform a variety of movement tasks while playing computer games. An important feature of the system is the ReJoyce Automated Hand Function Test (RAHFT). In this study we compared and validated the RAHFT against two widely-used clinical tests, the Action Research Arm Test (ARAT) [1][2] and the Fugl-Meyer Assessment (FMA) [3]. All three tests were performed in 34 separate sessions in 13 tetraplegic individuals. Principal component and regression analyses revealed that both the ARAT and the RAHFT correlated well with the first principle component fitted to the scores of the three tests. The FMA was less well correlated. These data help validate the RAHFT as a quantitative, automated alternative to the ARAT and FMA. The RAHFT is the first comprehensive test of hand function that does not depend on human judgment.
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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 | 0.005 |
| 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".