Pediatric Population Reference Value Distributions for Cancer Biomarkers: A CALIPER Study of Healthy Community Children
Bibliographic record
Abstract
As part of CALIPER program, a national research initiative aimed at closing the gaps in pediatric reference intervals, I sought to develop a database of covariate-stratified reference intervals in children for 11 circulating tumor markers in accordance with CLSI C28-A3 guidelines. Healthy children from birth to 18 years were recruited to participate in CALIPER and serum samples from 400-700 subjects were analyzed on the Abbott Architect ci4100 TM. Significant fluctuations in biomarker concentrations by age and/or gender were observed in 10 of 11 biomarkers. Age partitioning was required for CA 15-3, CA 125, CA 19-9, CEA, SCC, ProGRP, Total Free PSA, HE4 and AFP, and gender partitioning was required for CA 125, CA 19-9, Total Free PSA. The establishment of these reference intervals will aid in harnessing the full potential of tumor markers in a pediatric population and in research aimed at determining the clinical value of these markers.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".