Summary cortisol reactivity indicators: Interrelations and meaning
Bibliographic record
Abstract
Research on the hypothalamic pituitary adrenal (HPA) axis has involved a proliferation of cortisol indices. We surveyed recently published HPA-related articles and identified 15 such indices. We sought to clarify their biometric properties, specifically, how they interrelate and what they mean, because such information is rarely offered in the articles themselves. In the present article, the primary samples consist of community mothers and their infants (N = 297), who participated in two challenges, the Toy Frustration Paradigm and the Strange Situation Procedure. We sought to cross-validate findings from each of these samples against the other, and also against a clinically depressed sample (N = 48) and a sample of healthy older adults (N = 51) who participated in the Trier Social Stress Test. Cortisol was collected from all participants once before and twice after the challenges. These heterogenous samples were chosen to obtain the greatest possible range in cortisol levels and stress response regulation. Using these data, we computed the 15 summary cortisol indices identified in our literature survey. We assessed inter-relations amongst indices and determined their underlying dimensions via principal component analysis (PCA). The PCAs consistently extracted two components, accounting for 79%-93% of the variance. These components represent "total cortisol production" and "change in cortisol levels." The components were highly congruent across challenge, time, and sample. High variable loadings and explained factor variance suggest that all indices represent their underlying dimensions very well. Thus the abundance of summary cortisol indices currently represented in the literature appears superfluous.
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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 | 0.005 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".