Bibliographic record
Abstract
PURPOSE: This study aimed to assess the relationship between the severity of radiographic features and pain and function in patients with knee osteoarthritis (KOA). METHODS: Seventy-eight subjects (14 men, 64 women) with KOA, between the ages of 41 and 83 years (mean age, 61.29 years), were included. All the subjects diagnosed with KOA were scored for severity of radiographic KOA according to the Kellgren-Lawrence (K/L) grade, visual analogue scale (VAS), knee joint range of motion (ROM), Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC), maximum muscle power (MMP), and sit-to-stand (STS) and one-leg standing (OLS) tests. Associations among the K/L grade, diagnosis, pain, and function were examined by correlation analysis. RESULTS: There were no significant differences between the K/L grade, and the VAS, STS test time, and WOMAC scores (p>.05). There were no significant differences between the K/L grade, bilateral ROM, MMP, and left OLS test time (p>.05). However, there was a significant difference between the K/L grade and right OLS test time (p<.05). The K/L grade was negatively correlated with the left OLS test time(r=-.24, p<.05) and with the right OLS test time (r=-.307, p<.01). CONCLUSION: These results suggest that radiographic KOA was not associated with pain, knee MMP, ROM, and STS test time, but had a weak negative correlation with OLS test time.
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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 | 0.002 |
| 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 | 0.001 |
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".