Bibliographic record
Abstract
Background: The aim of this study was to investigate whether head-neck (H-N) position affects grip strength in healthy young adults and to find out, which H-N position have the greatest influence on grip strength. Methods: Eighty male and female students volunteered as subjects. The dominant hand was used to apply tension to the lever of a Jamar dynamometer. The data collection procedures followed American Society of Hand Therapists standardized grip-strength testing guidelines, with the except for H-N position. The maximal grip strength was measured at H-N in neutral, rotation to the left and rotation to the right. Result : The results were analyzed using independent ‘t’ test to compare the height and weight between groups. To compare the maximal grip strength between H-N position one-way analysis of variance and Tukey HSD was used. The result showed that maximal grip strength in the right dominant was significantly highest at H-N rotated to left at P < 0.05. Conclusion : The highest maximal grip strength obtained at H-N rotated to left, showed that for accurate assessment and rehabilitation, the H-N should be positioned opposite to the tested extremity which could be due to the influence of ATNR. J Neurol Res. 2012;2(3):93-98 doi: https://doi.org/10.4021/jnr117w
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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 | 0.000 | 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 | 0.000 |
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".