Updated <scp>J</scp>apanese growth references for infants and preschool children, based on historical, ethnic and environmental characteristics
Bibliographic record
Abstract
AIM: To provide updated growth references for Japanese children from birth to 6 years of age, for use in both growth monitoring and child care. METHODS: We analysed data from two national representative surveys that provided cross-sectional data on 3000 areas in the 2005 national census and longitudinal data from 136 hospitals. Growth references for length/height, weight, head circumference and chest circumference were constructed using the lambda-mu-sigma (LMS) method, with estimates of the L, M and S parameters. These updated values were then compared with growth references published by the World Health Organization. RESULTS: The 3rd, 50th and 97th smoothed percentile values of length/height, weight, head circumference and chest circumference for boys and girls from birth to 6 years are presented. The comparisons show some large differences in median measurements between the charts. CONCLUSION: Our growth references are based on a current, nationally representative sample of Japanese children. The results provide deep insight into child growth from a historical, ethnic and environmental point of view.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.010 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".