© 2010 Canadian Medical Association or its licensors
Bibliographic record
Abstract
Developmental coordination disorder is a neuro-developmental condition that affects 5%–6 % ofschool-aged children.1 Children with the disorder present with a range of coordination difficulties, including fine and gross motor problems,2 all of which interfere with normal daily activities, recreational activities and academic performance skills such as handwriting.3 Developmental coor-dination disorder is diagnosed when existing neurologic and physical problems are ruled out as the cause of motor coordi-nation difficulties and intellectual development has been taken into consideration (Box 1).1,4 The clinical implications of a diagnosis have been described previously.5 Because children with developmental coordination disor-der have been found to be less likely to participate in physical activities,6 it has been hypothesized that this condition may be a risk factor for obesity.7 Only a few studies have examined the association between motor coordination problems and overweight or obesity in children.7–10 Moreover, the literature in this area is limited in two key respects. First, previous research has relied almost exclusively on body mass index (BMI) as the outcome measure.8–10 Although important, BMI is not the only indicator of relative weight and has been shown to be weakly correlated with fat mass in young chil-dren.11,12 Waist circumference provides valid estimates of abdominal fat in pediatric populations13 and appears to be a stronger predictor of cardiovascular risk among children.14,15 Second, previous research in this area has been limited to cross-sectional data, with two notable exceptions.8,9 However, results from these two prospective studies were mixed: one study showed a significant effect of motor coordination on weight,8 the other did not.9 Our objective was to document several measures of adi-posity over time in children with and without developmental coordination disorder. Methods
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.006 | 0.004 |
| Insufficient payload (model declined to judge) | 0.879 | 0.799 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".