The Effect Of Combination Of Retrowalking Exercise And Static Contraction In Increasing Activity Daily Living Functions In Knee Osteoarthritis Risk Tea Pickers
Bibliographic record
Abstract
The tea picker job involves a lot of standing, wich puts pressure on the knees. This routine activity can cause musculoskeletal problems, such as osteoarthritis, which can reduce tea pickers’ daily living activity in tea pickers at risk of osteoarthritis which can be handled by retrowalking exercise and static contraction in increasing the function of daily living activity in tea pickers at risk of knee osteoarthritis. Research Methods: This study used a quasi – experimental design (one group desihn pre – test and post – test) involving 31 sampels of tea pickers. This research was cinducted for 4 weeks with 3 times a combination of retrowalking exercise and static contraction in a week. This study uses The Western Ontario and McMaster University Osteoarthritis Index (WOMAC) as an instrument to regulate daily living activity risk of knee osteoarthritis in tea pickers. Results : The test using the Paired Sample t Test showed a value of 0.000 (p < 0.05) which means that it has a normal contribution. Conclusion : There is an effect of a combination of retrowalking exercise and static contraction in increasing daily living activity risk of knee osteoarthritis in tea pickers. Suggestion : For future researchers, the result of study can be used as a reference for students, educator and physiotherapy regarding the effect of the combination of retrowalking exercise and static contraction on increasing the function of daily living activities in the risk takers of knee osteoarthritis.
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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) | 0.001 | 0.001 |
| 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 | 0.001 | 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".