CALIPER Hematology Reference Standards (I)
Bibliographic record
Abstract
Abstract Objectives Accurate hematologic test interpretation based on normative reference standards is critical to ensure appropriate clinical decision making. However, healthy pediatric reference data for most hematology parameters are lacking. To address this gap, this study establishes age- and sex-specific hematologic reference standards in the Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER) cohort of healthy children and adolescents. Methods Fresh whole blood samples collected from a total of 566 healthy children and adolescents (birth to <21 years) with informed consent were analyzed for 47 hematologic parameters on the Beckman Coulter DxH 900. Age- and sex-specific reference standards were calculated based on the Clinical and Laboratory Standards Institute guidelines. Results Reference value distributions for most hematology parameters demonstrated dynamic changes across the pediatric age range with significant age-specific differences observed for 39 of the 47 parameters examined. Sex-specific differences were also observed for eight hematologic parameters, primarily during and after puberty. Conclusions This study establishes a robust database of pediatric reference standards for 47 hematologic parameters in the CALIPER cohort for the first time. These comprehensive reference value data sets report potentially important and physiologically relevant trends in hematologic markers, clearly demonstrating the need for pediatric reference standards for hematologic test interpretation.
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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 | 0.018 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.007 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.006 |
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".