Technical note: Comparison of the maresh reference data with the who international standard for normal growth in healthy children
Bibliographic record
Abstract
The Maresh reference data on stature and long bone lengths in a sample of healthy middle-class children from Denver, Colorado [Maresh: Am J Dis Child 66 (1943) 227-257; Maresh: Am J Dis Child 89 (1955) 725-742; Maresh: Human growth and development (1970) p 155-200], have been used extensively by biological anthropologists to estimate juvenile age and body size using skeletal elements and to assess growth in skeletal series from different ethnic populations or archaeological cultural groups. How well these data reflect the potentially diverse growth patterns of healthy human populations from different geographic areas is unknown. Similarly, the efficacy of using the Maresh reference data to estimate stunting prevalence in prehistoric populations is unknown. This report presents the results from a comparison of the Maresh data on supine length and standing height to the World Health Organization (WHO) international child growth standard. The WHO growth standard is meant to depict typical human growth under optimal conditions and can be used to assess children worldwide, regardless of ethnicity and socioeconomic status. The results from this comparison indicate that although the Maresh reference data generally conform to the WHO standard, reflecting a normal human growth pattern, and therefore serve as a suitable reference for comparative studies of growth patterns, these reference data are not suitable for estimating stunting prevalence.
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 | 0.057 | 0.179 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.007 |
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".