Growth charts for Chinese Down syndrome children from birth to 14 years
Bibliographic record
Abstract
OBJECTIVE: To establish Down syndrome (DS)-specific growth charts for Hong Kong Chinese children. DESIGN AND SETTING: Growth data were collected from (1) members of the Hong Kong Down Syndrome Association (cross-sectional); (2) DS children attending special schools or living in residential homes (cross-sectional); and (3) the paediatric departments of seven public hospitals (retrospective). PATIENTS: 425 DS children (57% males and 43% females) born in 1977-2000, yielding 4987 observations. MAIN OUTCOME MEASURES: The LMS method was used to construct reference centile curves of weight, height, body mass index (BMI) from birth until 14 years and head circumference for the first 4 years. RESULTS: The median birth length was 49.8 cm and height at age 14 was 146.7 cm for DS boys. Corresponding figures for DS girls were 49.5 and 142.1 cm. The median birth weight was 3.0 kg for DS boys and 2.9 kg for DS girls. At age 14, 26% DS boys (BMI >22.6 kg/m(2)) and 12% DS girls (BMI >23.3 kg/m(2)) were overweight. The median head circumference at birth was 32.8 cm for boys and 32.0 cm for girls. CONCLUSIONS: Chinese DS children had a shorter stature, lower weight and tendency to be overweight than local non-DS children. Their growth patterns differed from those of Chinese DS children in Taiwan, and DS children in the USA and Sweden. Growth retardation was most salient during the first year of life.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".