Summary cortisol reactivity indicators: Interrelations and meaning
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it