Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: Accurate knowledge is central to effective self-care of osteoarthritis (OA). This study aimed to assess the measurement properties of the Osteoarthritis Knowledge Scale (OAKS) with versions for the hip and knee. METHODS: Participants with hip OA (n = 144), knee OA (n = 327), and no OA (n = 735) were recruited. Rasch analysis was conducted to assess psychometric properties using data from all participants with hip OA and 144 randomly selected participants with either knee OA or no OA. Test-retest reliability and measurement error were estimated among those with hip (n = 51) and knee (n = 142) OA. RESULTS: Four items from the draft scales were deleted following Rasch analysis. The final 11-item OAKS was unidimensional. Item functioning was not affected by gender, age, educational level, or scale version (hip or knee). Person separation index was 0.75. Test-retest intraclass correlation coefficient was 0.81 (95% CI 0.74, 0.86; hip version 0.66 [0.47, 0.79]; knee version 0.85 (0.79, 0.90)). Smallest detectable change was 9 points (scale range 11-55; hip OA version 11 points; knee OA version 8 points). CONCLUSION: The OAKS is a psychometrically adequate, unidimensional measure of important OA knowledge that can be used in populations with and without hip and knee OA. Caution is needed when using with populations with only hip OA as test-retest reliability of the hip version did not surpass the acceptable range.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 it