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Record W2059995600 · doi:10.1177/1099800402238334

Stress Hormones: How Do They Measure Up?

2002· review· en· W2059995600 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueBiological Research For Nursing · 2002
Typereview
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsRoyal College of Physicians and Surgeons of CanadaMount Royal University
Fundersnot available
KeywordsStressorStress (linguistics)Chronic stressAllostasisPsychological interventionPsychologyStress measuresPsychological stressHormoneMedicineClinical psychologyNeurosciencePsychiatryInternal medicine

Abstract

fetched live from OpenAlex

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.012
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.994
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.012
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.631
GPT teacher head0.511
Teacher spread0.120 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it