Approaches to Salivary Cortisol Collection and Analysis in Infants
Bibliographic record
Abstract
Salivary cortisol is becoming more commonly utilized as a biologic marker of stress in observational studies and intervention research. However, its use with infants (12 months of age or younger) is less widespread and poses some special challenges to researchers. In order to decide on the most suitable collection procedure for salivary cortisol in infants, a number of criteria should be considered. This article will aid investigators interested in integrating salivary cortisol measurement into their research studies by presenting (1) an overview of the patterns of cortisol secretion in infancy including the development of diurnal rhythm and response to stress; (2) a comparison of the most commonly used approaches for collecting salivary cortisol samples in infants including cotton rope, syringe aspiration technique, filter paper, hydrocellulose microsponge, and the Salimetrics children's swab; (3) a discussion of the factors contributing to heightened cortisol variability in infancy and how these can be limited; (4) analytical issues associated with cortisol measurement; and (5) examples of criteria to consider when choosing a saliva sampling method and lab for conducting assays.
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".