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Record W4415584746 · doi:10.17759/cpse.2025140308

Relationship of sleep characteristics with psychoneurophysiologic parameters in middle-aged and elderly individuals living in the European North of Russia

2025· article· ru· W4415584746 on OpenAlexaboutno aff
A.A. Mashyanova, Л. В. Поскотинова, Nikita A. Mitkin, Elena V. Krivonogova, Olga Krivonogova, Alexander V. Kudryavtsev

Bibliographic record

VenueClinical Psychology and Special Education · 2025
Typearticle
Languageru
FieldPsychology
TopicSleep and related disorders
Canadian institutionsnot available
FundersRussian Science Foundation
KeywordsCognitionSleep (system call)Depression (economics)Beck Depression InventoryMontreal Cognitive AssessmentCognitive impairmentInsomniaDementia

Abstract

fetched live from OpenAlex

<p>The <strong>objective</strong> of the study was to evaluate the correlation of sleep disorders with cognitive impairment, depression, and P300 cognitive evoked potential (EP) parameters in middle-aged and elderly individuals living in the European North. <strong>Methods and materials. </strong>A cross-sectional study was conducted in 2023–2024. A random sample of Arkhangelsk residents aged 45–74 years (N = 937) was observed. The Montreal Cognitive Function Assessment Scale (MoCa), Beck Depression Scale, a questionnaire for the assessment of subjective characteristics of sleep, electroencephalogram with registration of EP P300 parameters were used. <strong>Results.</strong> It was found that in both genders sleep disorders were associated with the presence of symptoms of depression. In women, sleep disorders were also associated with an age-associated increase in P300 EP latency, which may be an early sign of cognitive decline, and in men — with an increase in P300 EP amplitude, which is characteristic of anxiety-depressive disorders.</p>

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 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)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation 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 score0.082
Threshold uncertainty score0.740

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.069
GPT teacher head0.382
Teacher spread0.313 · 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 teacher head, 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

Citations0
Published2025
Admission routes1
Has abstractyes

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