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Record W3025348825

Cognitive functions and serum cortisol concentration in perimenopausal and postmenopausal women working non-manually.

2017· article· en· W3025348825 on OpenAlexaboutno aff
Dorota Raczkiewicz, Beata Sarecka‐Hujar, Alfred Owoc, Iwona Bojar

Bibliographic record

VenuePubMed · 2017
Typearticle
Languageen
FieldMedicine
TopicMenopause: Health Impacts and Treatments
Canadian institutionsnot available
Fundersnot available
KeywordsNeurocognitiveMenopauseCognitionPsychomotor learningPostmenopausal womenEffects of sleep deprivation on cognitive performanceMedicineInternal medicineVerbal memoryEndocrinologyPsychologyPsychiatry
DOInot available

Abstract

fetched live from OpenAlex

OBJECTIVES: To asses a possible relationship between serum cortisol concentration and cognitive function in peri- and postmenopausal women engaging in non-manual work. METHODS: The Montreal Cognitive Assessment (MoCA) was used to screen women for the study and the Computerized Neurocognitive-assessment Software (CNS) Vital Signs to diagnose cognitive functions. RESULTS: Cognitive functions and serum cortisol concentration did not differ between women in early and late perimenopause and postmenopause. The women in the study obtained lower reaction time compared to other cognitive functions studied. Cognitive functions correlated negatively with age and educational level, but not BMI. Serum cortisol concentration correlated negatively to NCI, motor speed, psychomotor speed and reaction time in postmenopausal women, but positively to complex memory in early perimenopausal women and to processing speed in early and late perimenopasal women. CONCLUSION: Higher serum cortisol concentration may negatively effect cognitive functions in women post menopause.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.039
GPT teacher head0.303
Teacher spread0.264 · 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

Citations5
Published2017
Admission routes1
Has abstractyes

Explore more

Same venuePubMed→Same topicMenopause: Health Impacts and Treatments→French-language works237,207→