An outcome measure for Japanese people with knee osteoarthritis.
Bibliographic record
Abstract
OBJECTIVE: We describe a new outcome measure for Japanese patients with knee osteoarthritis, the Japanese Knee Osteoarthritis Measure (JKOM). METHODS: The outcome measure was designed to incorporate the concepts of the World Health Organization's International Classification of Functioning, Disability and Health 2001, and to reflect the specific Japanese cultural lifestyle, which differs from Western countries. To examine the validity and reliability of this measure and to determine the underlying set of measures, psychometric measurements including factor analysis were conducted in comparison with 2 other health related scales, the Western Ontario and McMaster Universities Arthritis Index (WOMAC) and the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36). The following psychometric properties were tested with this new measure: test and retest reliability, internal consistency, content validity, construct validity, and criterion related validity. RESULTS: The measure was proved to have sufficient reliability and validity by means of statistical evaluation and comparison with other health related scales. Three domains are clearly separated on the loading pattern by factor analysis: pain, limitation in mobility related to daily activity, and restriction of participation in social life and health perception. CONCLUSION: The JKOM, a new knee OA measure, has sufficient reliability and validity for studies of the clinical outcomes of Japanese people with knee OA.
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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 | 0.005 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".