Approaches to Assessing Stressor‐Induced Cytokine and Endocrine Changes in Humans
Bibliographic record
Abstract
In humans, stressful events, more often than not, are fairly chronic, especially when one considers that apparently acute stressors have enduring psychological repercussions. It is important to consider the differential impacts of acute and chronic stressors. Field studies assessing the impact of stressors on immune and endocrine functioning are certainly more relevant to the analysis of wellbeing than studies conducted in contrived laboratory settings. Acute stressors of moderate severity increase, whereas severe stressors may reduce cytokine levels, as might a chronic stressor regimen. In humans, it is much more difficult to identify the impact of acute and chronic stressors in natural settings, as the acuteness of the stressor and its severity are often entwined. The relation between stress and diurnal cortisol changes is not a simple one, but instead varies as a function of the mood or pathological condition evoked.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".