Bibliographic record
Abstract
We appreciate the interest in our recently published CALIPER (Canadian Laboratory Initiative for Pediatric Reference Intervals)1 manuscripts and are delighted to see that the publications are stimulating further discussion in the field. Overall, the authors of these letters have raised several important questions, but they appear to have overlooked some important points when reviewing the published studies. They also fail to acknowledge the numerous limitations inherent in interpretation of cortisol as addressed in our published articles: namely, that circadian rhythms in infants differ from those of adults, that the stress of phlebotomy can alter cortisol concentrations, and that we examined a single time point in each individual within a large population of children rather than multiple time points in a small number of individuals. That being said, in our population, the reference intervals did not differ significantly between morning and afternoon. We did not seek to answer in our studies whether the influence of circadian rhythms could be observed within individuals, but rather, whether such a change could be observed across the population. Of course, our population is ethnically diverse and is representative of a healthy population in Ontario, Canada. Therefore, we believe that our conclusions are not altered by points raised in these letters. We agree that performing sequential sampling for cortisol measurement at multiple time points over 3–5 days would be ideal to assess the diurnal variation for cortisol. However, such a determination was well beyond the scope of the recently published CALIPER studies, which established reference value distributions in a large, healthy population of children.
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 | 0.009 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.005 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.127 | 0.083 |
| Insufficient payload (model declined to judge) | 0.019 | 0.015 |
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".