Description of children identified by physicians as having developmental coordination disorder
Bibliographic record
Abstract
The aim of this study was to describe in detail a large group of children aged 4 to 12 years who were diagnosed with developmental coordination disorder (DCD) by physicians following a rigorous multidisciplinary procedure. As part of a community-based DCD knowledge translation program, physicians received specialized training and were invited to identify children with probable DCD who were referred for further investigation to help confirm the diagnosis. Of 116 children (87 males, 29 females; age range 4y 1mo - 12y 11mo, mean age 8y) identified as having probable DCD by physician participants, 88 (76%) were subsequently diagnosed with DCD and 77.3% of these demonstrated a high degree of motor impairment. All children who were diagnosed experienced difficulties in self-care and/or academic or leisure activities. The male:female ratio was 3:1 and the incidence of preterm births among this sample was 12.5%. We conclude that, given the expense involved with ruling out differential diagnoses, it can be difficult to adhere rigorously to diagnostic criteria for DCD in clinical practice and research. This description of a group of children actually diagnosed with DCD helps to clarify the characteristics of these children as well as issues related to the refinement of diagnostic criteria.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".