Day-to-Day Reliability of Two Different Models to Quantify Knee Kinematics in Subjects With Knee Osteoarthritis and Healthy Controls
Bibliographic record
Abstract
Results from instrumented gait analysis vary between test situations. Subject characteristics and the biomechanical model can influence the total amount of variability. The purpose of this study was to quantify reliability of gait data in general, and with respect to the applied model, and investigated population group. Reliability was compared between a functional and a predictive gait model in subjects with knee osteoarthritis and healthy controls. Day-to-day consistency for sagittal plane variables was comparable between models and population groups. Transversal plane variables relative to joint excursion showed larger inconsistency for repeated measures, even for a more sophisticated biomechanical approach. In conclusion, the presented reliability data of sagittal plane kinematics should be used for a reasonable interpretation of results derived in clinical gait analysis. Variables of the transversal plane should not be used as long as sources of error are not sufficiently minimized.
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How this classification was reachedexpand
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".