Bibliographic record
Abstract
BACKGROUND AND PURPOSE: The present study evaluated the concurrent validity of the NK hand dexterity test (NKHDT) by use of three separate analyses: (1) the correlation between the NKHDT and a criterion comparator (Jebson's Hand Function Test (JHFT)); (2) the correlation between both dexterity tests and a patient-rated function questionnaire; and (3) the ability of subscales to differentiate between subjects with and without upper extremity pathology. METHOD: The study population included 40 individuals with a variety of musculoskeletal problems affecting the upper extremity and 10 individuals without any history of upper extremity problems. Both dexterity tests were administered on a single occasion according to a standard protocol. Subjects also completed a rating scale which evaluated self-care, household work, work and recreation on an 0-10-point scale. RESULTS: The validity of the NKHDT was supported in all three analyses because: (1) the correlation between the NKHDT and JHFT subtests was moderate to strong (Pearson's r = 0.47-0.87) and stronger when the objects were more similar in size; (2) both scales correlated to a similar extent with patient-rated function (Pearson's r = 0.34-0.67); and (3) all subscales were statistically different between subjects with and without upper extremity pathology (p < 0.01). CONCLUSIONS: The present study supports the use of the NKHDT as a measure of hand dexterity.
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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 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".