Effectiveness Of Jackknife Stretching On Hamstring Tightness With Low Back Pain Among Information Technology Professionals - Experimental Study
Bibliographic record
Abstract
Background: Hamstring muscles are located at the back of the thigh and the primary action of hamstring muscles is flexion of the knee. It is an effective self-stretching technique; it combines static and dynamic stretching and can be performed without any equipment. Methods: For Jack-knife stretching, participants started in a full squat position, gripping both ankles. The subjects were instructed to extend their knees as much as possible while bringing their chest close to their thighs, holding this position for 10 seconds before returning to the starting position6 . This sequence was repeated five times with a 10-second rest period between five repetitions, performed twice a week for two weeks. Results: Results shows that Jack Knife stretching is very effective in reducing Hamstring Tightness and reduction in low back pain. There is a significant difference in pre and post-intervention scores of NPRS with P < 0.001 and QUEBEC scores with improved functional ability having P < 0.001 Conclusion: The study concludes that Jack Knife stretching is effective in reducing Hamstring Tightness and reduction in low back pain. It was also concluded that there is increased functional ability of the Hamstring muscle
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".