Finger dexterity in well-functioning cohort of office workers in Macau
Bibliographic record
Abstract
Aim: The study aimed to describe the finger dexterity in office workers of an Asian population. Methods: One hundred twenty-seven right-handed office workers, aged 21-50 with a similar split of male and female, were recruited with finger dexterity measured by the O'Connor Finger Dexterity Test. The grip strength, tip and lateral pinch strength of both hands were also measured. Results: This study provided the percentile score of the O'Connor Finger Dexterity Test of both males and females in the Asian population. Raw scores of below 218 and 213 seconds in male and female participants respectively reach the 90th percentile, and above 237 and 235 seconds in male and female below the 10th percentile. Results showed no significant difference in local mean scores across different age groups, between male and female and with varying hours of working in typing, filing, and writing. A significant difference was only found in finger dexterity and years of working as office workers. No significant correlation was found between the finger dexterity with grip strength, tip and lateral pinch of the dominant right hand. The results were similar to the original normative score with similar work skills and demands. Conclusion: The mean scores could be used as a valid reference for local occupational therapists to evaluate the finger dexterity of office workers. However, caution has to be taken that conclusions drawn can be biased because of the relatively small sample size, and the results cannot be generalized to represent a wider Asian population.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".