Simple method for developing percentile growth curves for height and weight
Why this work is in the frame
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Bibliographic record
Abstract
The present paper demonstrates the ease of use of method I by Preece and Baine ([1978] Ann Hum Biol 5:1-24) in generating smoothed growth curves for both height and weight. Using the National Center for Health Statistics (NCHS) growth curve data, smoothed curves were developed and compared to those produced using the least-squares-cubic-spline method. Based on the lower sum of squares and better fit of shape as indicated by residual examination, it was concluded that the method I curve fitting procedure by Preece and Baine ([1978] Ann Hum Biol 5:1-24) fit centile growth curves for height and weight in 2-18-year-old male and female children as well as, if not better than, the least-squares-cubic-spline method used in developing the 1979 NCHS growth curves. Further, as this paper demonstrates, smoothed curves can be generated on a desktop computer using readily available software (the SOLVER function within Microsoft EXCEL).
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it