Individuals with knee osteoarthritis exhibit altered movement patterns during the sit-to-stand task
Bibliographic record
Abstract
Objectif : Determiner les strategies de compensation utilisees par les individus atteints de gonarthrose pour accomplir une tâche de transition assis-debout. Methode : Soixante-treize individus atteints de gonarthrose (âge moyenne : 69 ans) et 27 individus sains (âge moyenne : 66 ans) ont ete evalues lors d’une tâche de transition assis-debout a l’aide d’un systeme d’analyse de mouvement en trois dimensions. Des correlations ont ete calculees afin d’evaluer les differentes associations entre les parametres biomecaniques. Resultat : Les moments articulaires a la hanche et au genou montrent des correlations avec le temps d’execution de la tâche. Ces resultats suggerent que la hanche et le genou sont associes pour creer le moment specifique lors de l’execution de cette tâche. Le moment a la cheville et la flexion du tronc sont egalement correles. Ceci suggere une strategie de compensation pour atteindre la position debout. Si l’on compare les deux membres inferieurs, les moments aux hanches, aux genoux et aux chevilles sont asymetriques. Conclusion : D’apres les associations faibles a moderees obtenues entre les parametres biomecaniques lors de la tâche de transition assis-debout, il semble que des interactions plus complexes doivent probablement etre impliquees dans le developpement de strategies pour executer cette tâche par les individus atteints de gonarthrose.
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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 | 0.001 | 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) | 0.002 | 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".