Bibliographic record
Abstract
Stress as a stimulus is integral to dynamic homeostatic functioning. However, evidence of its potentially deleterious effects on health is mounting. The impetus to understand the mechanisms that underlie stress-related negative health outcomes and prevent the development of stress-related disorders has never been greater. Symptom severity and subjective levels of stress, although frequently assessed in studies of stress in nursing research, may not provide adequate data to fully understand the pervasive effects of chronic or overwhelming stress associated with stress disorders. The measurement of stress hormones such as cortisol can help identify bodily changes that are stressor specific, people at risk for development of stress-related disorders, and the efficacy of interventions aimed at stress reduction. Cortisol, as the peripheral output of one of the major stress response systems, possesses several properties that make its measurement highly useful for investigations of stress. This article discusses some of the biological mechanisms involved in the stress response, why cortisol is commonly measured, and issues and approaches in cortisol measurement.
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 | 0.011 | 0.017 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.005 | 0.010 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.005 | 0.008 |
| Insufficient payload (model declined to judge) | 0.002 | 0.004 |
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".