Indirect Estimation of Pediatric Between-Individual Biological Variation Data for 22 Common Serum Biochemistries
Why this work is in the frame
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Bibliographic record
Abstract
OBJECTIVES: Derivation of between-individual biological variation (CVg) data requires repeat sampling of the same subject, which is undesirable and challenging in children. We describe an indirect sampling (data mining) approach to obtain these data in children. METHODS: Twenty-two serum biochemistry results from 6,989 children, who visited their primary care physician in Queensland, Australia, and were tested only twice within a year were included. The CVg and index of individuality of the boys and girls were estimated by year of age, according to the procedures recommended by Fraser and Harris. RESULTS: The CVg was generally higher during the first year of life and declined to reach a constant level by age 4 to 6 years, except for aspartate aminotransferase, alanine aminotransferase, γ-glutamyltransferase, and phosphate. The CVg for these tended to increase after age 10 years. Most of the serum biochemistries examined in this study had indices of individuality 0.6 or less, except sodium, anion gap, bicarbonate, and chloride, which ranged from 0.6 to 1.4. The indices of individuality were very stable across all ages. CONCLUSIONS: These data are comparable to those reported by the Canadian Laboratory Initiative on Pediatric Reference Intervals study and the Ricos database for adults. This study reports the CVg trends and data for boys and girls by year of age, which have not been described previously.
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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 | 0.011 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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