Bibliographic record
Abstract
The purpose of this study was to identify the effects of mechanical traction applied to the knee joint on pain, knee range of motion (ROM), timed up and go (TUG) and Western Ontario and MacMaster Universities Osteoarthritis (WOMAC) in patients with knee osteoarthritis (KOA) of Kellgren-Lawrence radiological rating scale Ⅱ or Ⅲ. Twenty three patients participated in the experiment for a period of four weeks. After baseline assessment, the patients with KOA were randomized into two groups: the traction group (n1=12), which received traction with general physical therapy; and the control group (n2=11), which received general physical therapy only on unilateral knee joints. Patients received interventions once a day, three times a week, for four weeks. Wilcoxon signed-rank test was used to analyze the change of dependent variances within the group during pre and post intervention. Mann-Whitney U test was used to analyze the change of dependent variances as TUG and passive ROM between the two groups. Analysis of covariance was used to analyze the change of dependent variances as numeric pain rating scale (NPRS) and WOMAC score between the two groups. In Wilcoxon signed-rank test, the traction group improved significantly with regard to NPRS (p<.01), passive knee flexion ROM (p<.01), passive knee extension (p<.05), TUG (p<.01) and WOMAC scores (p<.01) after intervention for four weeks, but not for the control group. In the Mann-Whitney U test and analysis of covariance, no significant difference was seen among all the dependent variances after intervention for four weeks between the two groups. These outcomes suggest that further studies should be carried out to determine the effects of mechanical traction prior to using it for the treatment of patients with 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) | 0.000 | 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) | 0.002 | 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".