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Record W4405823938 · doi:10.54254/2753-8818/2024.18881

A Study on the Bi-directional Relationship Between Sleep Disturbance and Alzheimer’s Disease

2024· article· en· W4405823938 on OpenAlexaff
Xiaochun Su

Bibliographic record

VenueTheoretical and Natural Science · 2024
Typearticle
Languageen
FieldNeuroscience
TopicSleep and Wakefulness Research
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsDisturbance (geology)Alzheimer's diseaseDiseaseSleep disorderSleep (system call)NeurosciencePsychologyMedicineComputer scienceBiologyInternal medicineCognitionPaleontology

Abstract

fetched live from OpenAlex

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by gradual memory loss and cognitive decline. This multifactorial condition is influenced by aging, genetic predispositions, and various lifestyle factors. Among these, sleep has emerged as a critical component of overall health, with recent research highlighting a bi-directional relationship between sleep disturbances and AD. On one hand, poor sleep may contribute to the onset and progression of AD by exacerbating pathological processes; on the other hand, the accumulation of AD-related pathologies can further disrupt sleep. Notably, slow-wave sleep (SWS) has emerged as a key overlapping factor in this relationship. By examining the interplay between sleep disorders—such as insomnia, obstructive sleep apnea (OSA), and narcolepsy—and AD, this article seeks to deepen the understanding of their shared mechanisms. Ultimately, unraveling this complex relationship may provide new insights into the etiology of AD and pave the way for innovative treatment strategies aimed at mitigating the impact of sleep disturbances on disease progression.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.004
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.067
GPT teacher head0.350
Teacher spread0.283 · 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.

Study designTheoretical or conceptual
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
Published2024
Admission routes1
Has abstractyes

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