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Record W1965976205 · doi:10.1002/nur.20254

Using saliva to measure endogenous cortisol in nursing home residents with advanced dementia

2008· article· en· W1965976205 on OpenAlexaff
Diana Lynn Woods, Christine R. Kovach, Hershel Raff, Laura Joosse, Alicia Basmadjian, Kathleen Hegadoren

Bibliographic record

VenueResearch in Nursing & Health · 2008
Typearticle
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsSalivaMorningEveningDementiaMedicinePopulationPhysiologyEndogenyNursing homesCortisol awakening responseHydrocortisoneEndocrinologyGerontologyInternal medicineNursingEnvironmental healthDisease

Abstract

fetched live from OpenAlex

Two research teams determined the feasibility of saliva collection for cortisol measurement in nursing home residents with advanced dementia. Study aims were to: (a) determine if sufficient saliva could be obtained for assay and (b) examine whether cortisol values exhibited range and variability for meaningful interpretation. Useable samples were consistent across sites, suggesting that saliva collection for cortisol assay is a viable method in this setting. Cortisol values showed range and variability. More than half of the residents showed the normal adult pattern of high morning levels decreasing throughout the day. A third of the participants demonstrated an increase in the evening cortisol levels, while the remaining profiles were flat, suggesting hypothalamic-pituitary-adrenal (HPA) dysregulation in this population.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.277
GPT teacher head0.466
Teacher spread0.189 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations26
Published2008
Admission routes1
Has abstractyes

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