What we can learn from existing evidence about physical activity for juvenile idiopathic arthritis?
Bibliographic record
Abstract
The need for more rigorously designed trials to optimize the implementation of physical activity programmes Juvenile idiopathic arthritis (JIA) is one of the most common chronic conditions of childhood. Existing clinical practice guidelines (CPGs) for JIA illustrate the importance of care using both pharmacological and non-pharmacological interventions [1]. To date, however, CPGs including non-pharmacological interventions, such as physical activity (PA), have not been as rigorously developed as those for pharmacological interventions [1]. A recent systematic review on high-quality randomized controlled trials (RCTs) [2] revealed that a wide variety of structured PA programmes (i.e. cardio-karate [3], aquatics [4], pilates [5] and strength training [6,7]) are effective self-management therapy options for individuals with JIA. In comparison with a control, these PA programmes combined with pharmacotherapy have been shown to produce numerous positive health outcomes, such as reducing the number of actively inflamed joints (decrease in swollen and tender joint count) [3,4] and pain intensity [5], as well as improving joint range of motion [3,5], muscle strength [6], functional status [5,7] and quality of life [5,7].
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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 | 0.021 | 0.076 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.004 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.017 | 0.026 |
| Insufficient payload (model declined to judge) | 0.008 | 0.005 |
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".